Michael L. Anderson, Ph.D.

Department of Psychology

Institute for Advanced Computer Studies

Franklin & Marshall College

Program in Neuroscience and Cognitive Science

Lancaster, PA 17604

University Of Maryland

michael -dot- anderson -at- fandm -dot- edu

College Park, MD 20742


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Books

Metacognition in Computation: Papers from the 2005 AAAI Spring Symposium. Michael L. Anderson and Tim Oates, eds. (Menlo Park, CA: AAAI Press, 2005).
  Abstract:The importance of metacognition in human thinking, learning, and problem solving is well established. Humans use metacognitive monitoring and control to choose goals, assess their own progress, and, if necessary, adopt new strategies for achieving those goals, or even abandon a goal entirely. For instance, students preparing for an examination will make judgments about the relative difficulty of the material, and use this to choose study strategies. Since in such cases accuracy of metacognitive judgments correlates with academic performance, understanding human metacognition has been an important part of work on automated tutoring systems, and has led to the use of computer assistants that help improve human metacognition.

However, there has also been growing interest in trying to create, and investigate the potential benefits of, intelligent systems which are themselves metacognitive. It is thought that systems that monitor themselves, and proactively respond to problems, can perform better, for longer, with less need for (expensive) human intervention. Thus has IBM widely publicized their "autonomic computing" initiative, aimed at developing computers which are (in their words) self-aware, self-configuring, self-optimizing, self-healing, self-protecting, and self-adapting. More ambitiously, it is hypothesized that metacognitive awareness may be one of the keys to developing truly intelligent artificial systems. DARPA's recent Cognitive Information Processing Technology initiative, for instance, foregrounds reflection (along with reaction and deliberation) as one of the three pillars required for flexible, AI systems.

On the other side of the coin, it has also been established that metacognition can actually interfere with performance. Metacognition is no panacea, and therefore one of the issues that require further inquiry is the scope and limits of its usefulness.

Content and Comportment: On Embodiment and the Epistemic Availability of the World. Michael O'Donovan-Anderson (Lanham, MD: Rowman & Littlefield, 1997).
  Abstract:Content and Comportment argues that the answer to some long-standing questions in epistemology and metaphysics lies in taking up the neglected question of the role of our bodily activity in establishing connections between representational states--knowledge and belief in particular--and their objects in the world. It takes up these ideas from both current mainstream analytic philosophy--Frege, Dummett, Davidson, Evans--and from mainstream continental work--Heidegger and his commentators and critics.

The Incorporated Self: Interdisciplinary Perspectives on Embodiment. Michael O'Donovan-Anderson, ed. (Lanham, MD: Rowman & Littlefield, 1996).
  Abstract: The Incorporated Self demonstrates that although embodiment has long been a central concern of the theoretical humanities, its potential to alter epistemology and open up new areas of dualistic inquiry has not been pursued far enough. This anthology collects the the works of scholars from a broad range of disciplines, each examining the nature of the body and the necessity of embodiment to the human experience--for our self awareness, our sense of identity, and the workings of the mind.

 

Journal Articles / Book Chapters

Eroding the boundaries of cognition: Implications of embodiment.. Michael Anderson, Michael Richardson, and Anthony Chemero (in press). Topics in Cognitive Science
  Abstract: To accept that cognition is embodied is to question many of the beliefs traditionally held by cognitive scientists. One key question regards the localization of cognitive faculties. Here we argue that for cognition to be embodied and sometimes embedded, means that the cognitive faculty cannot be localized in a brain area alone. We review recent research on neural reuse, the 1/f structure of human activity, tool use, group cognition and social coordination dynamics that we believe demonstrates how the boundary between the different areas of the brain, the brain and body, and the body and environment is not only blurred, but indeterminate. In turn, we propose that cognition is supported by a nested structure of task-specific synergies, which are softly assembled from a variety of neural, bodily and environmental components (including other individuals), and exhibit interaction dominant dynamics.

Neural reuse in the evolution and development of the brain: Evidence for developmental homology?. Michael Anderson & Marcie Penner-Wilger in press.
  Abstract: This paper lays out some of the empirical evidence for the importance of neural reuse—the reuse of existing (inherited and/or early-developing) neural circuitry for multiple behavioral purposes—in defining the overall functional structure of the brain. We then discuss in some detail one particular instance of such reuse: the involvement of a local neural circuit in finger awareness, number representation, and other diverse functions. Finally, we consider whether and how the notion of a developmental homology can help us understand the relationships between the cognitive functions that develop out of shared neural supports.

Comparing Matrix Decomposition Methods for Meta-Analysis and Reconstruction of Cognitive Neuroscience Results. Kevin Gold, Catherine Havasi, Michael Anderson, Kenneth Arnold, AAAI 2011
  Abstract:The results of 2,256 neuroimaging experiments were analyzed using singular value decomposition (SVD) and non-negative matrix factorization (NMF) to extract pat- terns in the data. To evaluate the techniques’ efficacy at capturing regularities in the data, one positive and one negative result from each of 100 random experiments were treated as missing, and the values were iteratively reconstructed using each technique for dimensionality reduction. Under the best conditions, precision and recall of roughly 78% was achieved for each method. Weight- ing the domain matrix and area matrix to have equal first eigenvalues before combining them, a technique known as blending, significantly improved results for both methods. While using unnormalized data appeared to produce a peak in results for 10-15 dimensions, normalizing to take into account variation in the popularity of experiment types removed the effect. The basis vectors produced by each method do not support the idea that current cognitive ontologies map well to individual brain areas.

Conceptual discontinuity involves recycling old processes in new domains. Commentary on The Origin of Concepts, by Susan Carey. . David Landy, Colin Allen, Michael Anderson, Commentary on The Origin of Concepts by Carey, 2011
  Abstract:We dispute Carey’s assumption that distinct core cognitive processes employ domain-specific input analyzers to construct proprietary representations. We give reasons to believe that conceptual systems co-opt core components for new domains. Domain boundaries, as well as boundaries between perceptual – motor and conceptual cognitive resources may be useful abstractions, but do not appear to reflect constraints respected by brains and cognitive systems.

The Metacognitive Loop and Reasoning about Anomolies. Matthew D. Schmill, Michael L. Anderson, Scott Fults, Darsana Josyula, Tim Oates, Don Perlis, Hamid Shahri, Shomir Wilson, and Dean Wright in Metareasoning: Thinking about Thinking, pg. 183-198, 2011.
  Abstract: Describes a generalized metacognitive layer aimed at providing ness to autonomous systems in the face of unforeseen perturbations. The metacognitive loop encodes commonsense knowledge about how AI systems fail in the form of a Bayesian network and uses that network to reason abstractly about what to do when a system's expectations about its own actions are violated. Our aim is to provide an engineering methodology for developing metalevel interoperable AI systems and in so doing provide the benefit of adding reactive anomaly-handling using the MCL library. Also introduces a system architecture with a number of interacting cognitive components at the object level that we believe is a useful testbed for metacognitive research.

An Approach to Human-level Commonsense Reasoning. Michael L. Anderson, Walid Gomaa, John Grant & Don Perlis to appear in Logic, Epistemology, and the Unity of Science, 2011.
  Abstract: Commonsense reasoning has proven exceedingly difficult both to model and to im- plement in artificial reasoning systems. This paper discusses some of the features of human reasoning that may account for this difficulty, surveys a number of reasoning systems and formalisms, and offers an outline of active logic, a non-classical para- consistent logic that may be of some use in implementing commonsense reasoning.

Neural reuse: A fundamental organizational principle of the brain. Michael Anderson. Behavioral and Brain Sciences, pg. 245-313, 2010.
  Abstract: An emerging class of theories concerning the functional structure of the brain takes the reuse of neural circuitry for various cognitive purposes to be a central organizational principle. According to these theories, it is quite common for neural circuits established for one purpose to be exapted (exploited, recycled, redeployed) during evolution or normal development, and be put to different uses, often without losing their original functions. Neural reuse theories thus differ from the usual understanding of the role of neural plasticity (which is, after all, a kind of reuse) in brain organization along the following lines: According to neural reuse, circuits can continue to acquire new uses after an initial or original function is established; the acquisition of new uses need not involve unusual circumstances such as injury or loss of established function; and the acquisition of a new use need not involve (much) local change to circuit structure (e.g., it might involve only the establishment of functional connections to new neural partners). Thus, neural reuse theories offer a distinct perspective on several topics of general interest, such as: the evolution and development of the brain, including (for instance) the evolutionary-developmental pathway supporting primate tool use and human language; the degree of modularity in brain organization; the degree of localization of cognitive function; and the cortical parcellation problem and the prospects (and proper methods to employ) for function to structure mapping. The idea also has some practical implications in the areas of rehabilitative medicine and machine interface design.

Investigating functional cooperation in the human brain using simple graph-theoretic methods. Michael L. Anderson, Joan Brumbaugh and Aysu Suben. In: W. Chaovalitwongse, P. Pardalos and P. Xanthopoulos, eds. Computational Neuroscience, Springer, 2010, pages 31-42.
  Abstract: This chapter introduces a very simple analytic method for mining large numbers of brain imaging experiments to discover functional cooperation between regions. We then report some preliminary results of its application, illustrate some of the many future projects in which we expect the technique will be of considerable use (including a way to relate fMRI to EEG), and describe a research resource for investigating functional cooperation in the cortex that will be made publicly available through the lab web site. One significant finding is that differences between cognitive domains appear to be attributable more to differences in patterns of cooperation between brain regions, rather than to differences in which brain regions are used in each domain. This is not a result that is predicted by prevailing localization-based and modular accounts of the organization of the cortex.

The Origins of Collective Overvaluation: Irrational exuberance emerges from simple, honest and rational individual behavior. Michael L. Anderson and C. Athena AktipisProceedings of the 32nd Annual Meeting of the Cognitive Science Society, 2009.
  Abstract: The generation of value bubbles is an inherently psychological and social process, where information sharing and individual decisions can affect representations of value. Bubbles occur in many domains, from the stock market, to the runway, to the laboratories of science. Here we seek to understand how psychological and social processes lead representations (i.e., expectations) of value to become divorced from the inherent value, using asset bubbles as an example. Using an agent-based model we explore whether a simple switching rule can generate irrational exuberance, and systematically explore how communication between decision makers influences the speed and intensity of overvaluation. We show that rational and simple individual level rules combined with honest information sharing are sufficient to generate the collective overvaluation characteristic of irrational exuberance. Further, our results demonstrate that simple noise in the exchange of value information leads to rapidly increasing expectations about value, even when no one is engaged in exaggerating their expectations for the assets they own.

"What puts the 'meta' in metacognition?" Commentary on How we know our minds, by Peter Carruthers. Michael L. Anderson and Don Perlis. Behavioral and Brain Sciences, 32(2), 138-139, 2009.
  Abstract: This commentary suggests an alternate definition for metacognition, as well as an alternate basis for the “aboutness” relation in representation. These together open the way for an understanding of mindreading that is significantly different from the one advocated by Carruthers.

Affordances and intentionality: Reply to Roberts. Michael L. Anderson and Tony Chemero. Journal of Mind and Behavior, 30(4), 2009.
  Abstract: In this essay we respond to some criticisms of the Guidance Theory of Representation offered by Tom Roberts. We argue that although Robertsù criticisms miss their mark, he raises the important issue of the relationship between affordances and the action-oriented representations proposed by the Guidance Theory. Affordances play a prominent role in the anti-representationalist accounts offered by theorists of embodied cognition and ecological psychology, and the Guidance Theory is motivated in part by a desire to respond to the critiques of representationalism offered in such accounts, without giving up entirely on the idea that representations are an important part of the cognitive economy of many animals. Thus, explorations of whether and how such accounts can in fact be related and reconciled potentially offer to shed some light on this ongoing controversy. Although the current essay hardly settles the larger debate, it does suggest that there may be more possibility for agreement than is often supposed.

What mindedness is. Michael L. Anderson, Europe's Journal of Psychology, November, 2009.
  Abstract: Recent advances in theoretical cognitive science can be fruitfully characterized as part of the ongoing attempt to come to grips with the very idea of homo sapiens--an entity at once biological and intelligent--and among the more striking developments has been the emergence of a philosophical anthropology that, contra Descartes and his thinking thing, instead puts doing at the center of human being. This shift to a more "enactive" understanding of human nature is owed proximally to the work of Heidegger and Merleau-Ponty, but also has clear precursors in such figures as William James and Hegel--and more specifically Marx and Marxist interpreters of Hegel such as Kojeve. Naturally, Darwin must be considered as central as any philosopher, and many of the recent developments also echo the Aristotelian sense that being-at-work is the primary way of being anything at all.

Are interactive specialization and massive redeployment compatible?. Michael L. Anderson, Commentary on Neuroconstructivism by Sirois et. al., 2008
  Abstract:I offer a simple method for further investigating the Interactive Specialization framework, and some data that may or may not be compatible with the approach, depending on the precise meaning of “specialization.” Findings from my lab indicate that, while networks of brain areas cooperate in specialized ways to support cognitive functions, individual brain areas participate in many such networks, in different cognitive domains.

Brain network analysis of seizure . Wanpracha A. Chaovalitwongse, Wichai Suharitdamrong, Chang-Chia Liu and Michael L. Anderson Ann. Zool. Fennici, 45(5): 402-14, 2008.
  Abstract: The human brain is one of the most complex biological systems. Neuroscientists seek to understand the brain function through detailed analysis of neuronal excitability and synaptic transmission. In this study, we propose a network analysis framework to study the evolution of epileptic seizures. We apply a signal processing approach, derived from information theory, to investigate the synchronization of neuronal activities, which can be captured by electroencephalogram (EEG) recordings. Two networktheoretic approaches are proposed to globally model the synchronization the brain network. We observe some unique patterns related to the development of epileptic seizures, which can be used to illuminate the brain function governed by the epileptogenic process during the period before a seizure. The proposed framework can provide a global structural patterns in the brain network and may be used in the simulation study of dynamical systems (like the brain) to predict oncoming events (like seizures). To analyze long-term EEG recordings in the future, we discuss how the Markov-Chain Monte Carlo (MCMC) methodology can be applied to estimate the clique parameters. This MCMC framework fits very well with this work as the epileptic evolution can be considered to be a system with unobservable state variables and nonlinearities.

Circuit sharing and the implementation of intelligent systems. Michael L. Anderson. Connection Science, 20(4): 239-51, 2008.
  Abstract: One of the most foundational and continually contested questions in the cognitive sciences is the degree to which the functional organization of the brain can be understood as modular. In its classic formulation, a module was defined as a cognitive sub-system with (all or most of) nine specific properties; the classic module is, among other things, domain specific, encapsulated (i.e. maintains proprietary representations to which other modules have no access), and implemented in dedicated neural substrates. Most of the examinations—and especially the criticisms—of the modularity thesis have focused on these properties individually, for instance by finding counterexamples in which otherwise good candidates for cognitive modules are shown to lack domain specificity or encapsulation. The current paper goes beyond the usual approach by asking what some of the broad architectural implications of the modularity thesis might be, and attempting to test for these. The evidence does not favor a modular architecture for the cortex. Moreover, the evidence suggests that best way to approach the understanding of cognition is not by analyzing and modelling different functional domains (visual perception, attention, language, motor control, etc.) in isolation from the others, but rather by looking for points of overlap in their neural implementations, and exploiting these to guide the analysis and decomposition of the functions in question. This has significant implications for the question of how to approach the design and implementation of intelligent artifacts in general, and language-using robots in particular.

On the grounds of x-grounded cognition. Michael L. Anderson. In: P. Calvo and T. Gomila, eds. The Elsevier Handbook of Cognitive Science: An Embodied Approach, pp. 423-35, 2008.
  Abstract: In this chapter, I lay down a challenge to the field of embodied/situated cognition. I argue we must move beyond the too simple task of finding evidence against abstract, amodal, and cognitivist theories of cognition and focus on detailing and supporting specific accounts of the functional inheritances that abstract higher order cognition has received from the substrates on which it is built. The chapter included a discussion of the massive redeployment hypothesis, and its significance for embodied cognition.

Active logic semantics for a single agent in a static world. Michael L. Anderson, Walid Gomaa, John Grant and Don Perlis. Artificial Intelligence 172: 1045-63, 2008.
  Abstract: For some time we have been developing, and have had significant practical success with, a time-sensitive, contradiction-tolerant logical reasoning engine called the active logic machine (ALMA). The current paper details a semantics for a general version of the underlying logical formalism, active logic. Central to active logic are special rules controlling the inheritance of beliefs in general (and of beliefs about the current time in particular), very tight controls on what can be derived from direct contradictions (P &P), and mechanisms allowing an agent to represent and reason about its own beliefs and past reasoning. Furthermore, inspired by the notion that until an agent notices that a set of beliefs is contradictory, that set seems consistent (and the agent therefore reasons with it as if it were consistent), we introduce an “apperception function” that represents an agent’s limited awareness of its own beliefs, and serves to modify inconsistent belief sets so as to yield consistent sets. Using these ideas, we introduce a new definition of logical consequence in the context of active logic, as well as a new definition of soundness such that, when reasoning with consistent premises, all classically sound rules remain sound in our new sense. However, not everything that is classically sound remains sound in our sense, for by classical definitions, all rules with contradictory premises are vacuously sound, whereas in active logic not everything follows from a contradiction.

Content and action: The guidance theory of representation. Michael L. Anderson, Gregg Rosenberg. In: D. Smith (ed) Evolutionary Biology and the Central Problems of Cognitive Science, a special issue of Journal of Mind and Behavior, 29(1-2): 55-86, 2008.
  Abstract: The current essay introduces the guidance theory of representation, according to which the content and intentionality of representations can be accounted for in terms of the way they provide guidance for action. The guidance theory offers a way of fixing representational content that gives the causal and evolutionary history of the subject only an indirect (non-necessary) role, and an account of representational error, based on failure of action, that does not rely on any such notions as proper functions, ideal conditions, or normal circumstances. Moreover, because the notion of error is defined in terms of failure of action, the guidance theory meets the “meta-epistemological requirement” that representational error should be potentially detectable by the representing system itself. In this essay, we offer a brief account of the biological origins of representation, a formal characterization of the guidance theory, some examples of its use, and show how the guidance theory handles some traditional problem cases for representation: the problems of error and of representation of fictional and abstract entities. Being both representational and action-grounded, the guidance theory may provide some common ground between embodied and cognitivist approaches to the study of the mind.

A self-help guide for autonomous systems. Michael L. Anderson, Scott Fults, Darsana P. Josyula, Tim Oates, Don Perlis, Matt D. Schmill, Shomir Wilson and Dean Wright. AI Magazine, 29(2): 67-76, 2008.
  Abstract: Humans learn from their mistakes. When things go badly, we notice that something is amiss, figure out what went wrong and why, and attempt to repair the problem. Artificial systems depend on their human designers to program in responses to every eventuality and therefore typically don't even notice when things go wrong, following their programming over the proverbial, and in some cases literal, cliff. This article describes our past and current work on the metacognitive loop, a domain-general approach to giving artificial systems the ability to notice, assess, and repair problems. The goal is to make artificial systems more robust and less dependent on their human designers.

Evolution, embodiment and the nature of the mind. Michael L. Anderson. In: B. Hardy-Vallee & N. Payette, eds. Beyond the brain: embodied, situated & distributed cognition. (Cambridge: Cambridge Scholar's Press), pages 15-28, 2008.
  Abstract: In this article, I do three main things:

1. First, I introduce an approach to the mind motivated primarily by evolutionary considerations. I do that by laying out four principles for the study of the mind from an evolutionary perspective, and four predictions that they suggest. This evolutionary perspective is completely compatible with, although broader than, the embodied cognition approach.

2. Then I look at one prediction in depth, the idea that the brain evolved by exaptation--reusing exiting functional units, and combining them in novel ways to generate new cognitive capacities.

3. Finally, I try to lay out some of the implications, both of the in-depth example, and of the more general approach.

Application of MCL in a dialog agent. Darsana P. Josyula, Scott Fults, Michael L. Anderson, Shomir WIlson, Don Perlis. 2007.
  Abstract: In this article, I do three main things:

1. First, I introduce an approach to the mind motivated primarily by evolutionary considerations. I do that by laying out four principles for the study of the mind from an evolutionary perspective, and four predictions that they suggest. This evolutionary perspective is completely compatible with, although broader than, the embodied cognition approach.

2. Then I look at one prediction in depth, the idea that the brain evolved by exaptation--reusing exiting functional units, and combining them in novel ways to generate new cognitive capacities.

3. Finally, I try to lay out some of the implications, both of the in-depth example, and of the more general approach.

Massive redeployment, exaptation, and the functional integration of cognitive operations. Michael L. Anderson. Synthese, 159(3): 329-345, 2007.
  Abstract: The massive redeployment hypothesis (MRH) is a theory about the functional topography of the human brain, offering a middle course between strict localization on the one hand, and holism on the other. Central to MRH is the claim that cognitive evolution proceeded in a way analogous to component reuse in software engineering, whereby existing components-originally developed to serve some specific purpose-were used for new purposes and combined to support new capacities, without disrupting their participation in existing programs. If the evolution of cognition was indeed driven by such exaptation, then we should be able to make some specific empirical predictions regarding the resulting functional topography of the brain. This essay discusses three such predictions, and some of the evidence supporting them. Then, using this account as a background, the essay considers the implications of these findings for an account of the functional integration of cognitive operations. For instance, MRH suggests that in order to determine the functional role of a given brain area it is necessary to consider its participation across multiple task categories, and not just focus on one, as has been the typical practice in cognitive neuroscience. This change of methodology will motivate (even perhaps necessitate) the development of a new, domain-neutral vocabulary for characterizing the contribution of individual brain areas to larger functional complexes, and direct particular attention to the question of how these various area roles are integrated and coordinated to result in the observed cognitive effect. Finally, the details of the mix of cognitive functions a given area supports should tell us something interesting not just about the likely computational role of that area, but about the nature of and relations between the cognitive functions themselves. For instance, growing evidence of the role of "motor" areas like M1, SMA and PMC in language processing, and of "language" areas like Broca's area in motor control, offers the possibility for significantly reconceptualizing the nature both of language and of motor control.

A review of recent research in reasoning and metareasoning. Michael L. Anderson, Tim Oates. AI Magazine, 28(1): 7-16, 2007. Article featured on the cover of AI Magazine!
  Abstract: Recent years have seen a resurgence of interest in the use of metacognition in intelligent systems. This essay is part of a small section meant to give interested researchers an overview and sampling of the kinds of work currently being pursued in this broad area. The current essay offers a review of recent research in two main topic areas: the monitoring and control of reasoning (metareasoning) and the monitoring and control of learning (metalearning).

Evolution of cognitive function via redeployment of brain areas. Michael L. Anderson. The Neuroscientist, 13(1): 13-21, 2007.
  Abstract: The creative re-use of existing neural components may have played a significant role in the evolutionary development of cognition. There are obvious evolutionary advantages to such redeployment, and the data presented here confirm three important empirical predictions of this account of the development of cognition: (1) a typical brain area will be utilized by many cognitive functions in diverse task categories, (2) evolutionarily older brain areas will be deployed in more cognitive functions and (3) more recent cognitive functions will utilize more, and more widely scattered brain areas. These findings have implications not just for our understanding of the evolutionary origins of cognitive function, but also for the practice of both clinical and experimental neuroscience.

The massive redeployment hypothesis and the functional topography of the brain. Michael L. Anderson. Philosophical Psychology, 21(2): 143-174, 2007.
  Abstract: This essay introduces the massive redeployment hypothesis, an account of the functional organization of the brain that centrally features the fact that brain areas are typically employed to support numerous functions. The massive redeployment hypothesis is supported by three case studies of redeployment, and compared and contrasted with other theories of the localization of function.

How to study the mind: An introduction to embodied cognition. Michael L. Anderson. In F.Santoianni and C. Sabatano, eds. Brain Development in Learning Environments: Embodied and Perceptual Advancements , Cambridge Scholars Press, pages 65-82, 2007.
  Abstract: Embodied Cognition (EC) is a comprehensive approach to, and framework for, the study of the mind. EC treats cognition as a coordinated set of tools evolved by organisms for coping with their environments. Each of the key terms in this characterization-tool, evolved, organism, coping, and environment-has a special significance for understanding the mind that is discussed in this article.

The metacognitive loop I: Enhancing reinforcement learning with metacognitive monitoring and control for improved perturbation tolerance (preprint, published version). Michael L. Anderson, Tim Oates, Waiyian Chong and Don Perlis Journal of Experimental and Theoretical Artificial Intelligence, 18(3): 387-411, 2006.
  Abstract: Maintaining adequate performance in dynamic and uncertain settings has been a perennial stumbling-block for intelligent systems. Nevertheless, any system intended for real-world deployment must be able to accommodate unexpected change--that is, it must be perturbation-tolerant. We have found that meta-cognitive monitoring and control--the ability of a system to self-monitor its own decision-making processes and ongoing performance, and to make targeted changes to its beliefs and action-determining components--can play an important role in helping intelligent systems cope with the perturbations that are the inevitable result of real-world deployment. In this paper we present the results of several experiments demonstrating the efficacy of metacognition in improving the perturbation tolerance of reinforcement learners, and discuss a general theory of metacognitive monitoring and control, in a form we call the metacognitive loop (MCL)

Cognitive science and epistemic openness (preprint, published version). Michael L. Anderson. Phenomenology and the Cognitive Sciences, 5(2): 125-154, 2006.
  Abstract: Recent findings in cognitive science suggest that the epistemic subject is more complex and epistemically porous than is generally pictured. Human knowers are open to the world via multiple channels, each operating for particular purposes and according to its own logic. These findings need to be understood and addressed by the philosophical community. The current essay argues that one consequence of the new findings is to invalidate certain arguments for epistemic anti-realism.

Designing a Universal Interfacing Agent. (preprint, ) Darsana P. Josyula, Michael L. Anderson and Don Perlis, , 2005.
  Abstract: This paper argues the need for a universal interfacing agent that users can use to control different task-oriented systems. It discusses the different capabilities required of such an agent and what is required for implementing those capabilities. In addition, it provides an approach for its implementation.

The roots of self-awareness. (preprint, published version) Michael L. Anderson and Don Perlis. Phenomenology and the Cognitive Sciences, 4(3): 297-333, 2005.
  Abstract: In this paper we provide an account of the structural underpinnings of self-awareness. We offer both an abstract, logical account-by way of suggestions for how to build a genuinely self-referring artificial agent-and a biological account, via a discussion of the role of somatoception in supporting and structuring self-awareness more generally. Central to the account is a discussion of the necessary motivational properties of self-representing mental tokens, in light of which we offer a novel definition of self-representation. We also discuss the role of such tokens in organizing self-specifying information, which leads to a naturalized restatement of the guarantee that introspective awareness is immune to error due to mis-identification of the subject.

Logic, self-awareness and self-improvement: The metacognitive loop and the problem of brittleness. (preprint, published version) Michael L. Anderson and Donald R. Perlis. Journal of Logic and Computation, 15(1), 2005. The #1 most read article from Journal of Logic and Computation for 2005; top 5 for 2006!
  Abstract: This essay describes a general approach to building perturbation-tolerant autonomous systems, based on the conviction that artificial agents should be able notice when something is amiss, assess the anomaly, and guide a solution into place. We call this basic strategy of self-guided learning the metacognitive loop; it involves the system monitoring, reasoning about, and, when necessary, altering its own decision-making components. In this essay, we (a) argue that equipping agents with a metacognitive loop can help to overcome the brittleness problem, (b) detail the metacognitive loop and its relation to our ongoing work on time-sensitive commonsense reasoning, (c) describe specific, implemented systems whose perturbation tolerance was improved by adding a metacognitive loop, and (d) outline both short-term and long-term research agendas.

A Flexible Approach to Quantifying Various Dimensions of Environmental Complexity. () Michael L. Anderson, 2004.
  Abstract: /b>In this paper I propose a flexible method of quantifying various dimensions of the complexity of a test environment, including its information density, variability, volatil- ity, inconsistency, and uncertainty. This allows one to determine the task performance of intelligent agents as a function of such measures, and therefore permits derivative measures of their perturbation tolerance—that is, their ability to cope with a complex and changing environment. <

Embodied cognition: A field guide. Michael L. Anderson. Artificial Intelligence 149(1):91-130, 2003.
An Artificial Intelligence top 10 most downloaded article for 2003; top 25 for 2004, 2006 and 2008!
 

Abstract: The nature of cognition is being re-considered. Instead of emphasizing formal operations on abstract symbols, the new approach foregrounds the fact that cognition is, rather, a situated activity, and suggests that thinking beings ought therefore be considered first and foremost as acting beings. The essay reviews recent work in Embodied Cognition, provides a concise guide to its principles, attitudes and goals, and identifies the physical grounding project as its central research focus.

Representations, symbols and embodiment. Michael L. Anderson. Artificial Intelligence 149(1):151-6, 2003.
An Artificial Intelligence top 25 most downloaded article for 2003!
 

Abstract: Response to "Embodied artificial intelligence", a commentary by Ron Chrisley.

Prelinguistic agents will form only egocentric predicates. Michael L. Anderson and Tim Oates. Behavioral and Brain Sciences 26(3):284-5, 2003. (Commentary on The neural basis of predicate-argument structure by James Hurford)
  Abstract: The representations formed by the ventral and dorsal streams of a prelinguistic agent will tend to be too qualitatively similar to support the distinct roles required by PREDICATE(x) structure. We suggest that the attachment of qualities to objects is not a product of the combination of these separate processing streams, but is instead a part of the processing required in each. In addition, we suggest that the formation of objective predicates is inextricably bound up with the emergence of language itself, and so cannot be cleanly identified with any prelinguistic cognitive capacities.

Symbol systems. Michael L. Anderson and Donald R. Perlis. Encyclopedia of Cognitive Science (New York: Nature Publishing Group), 2002.
  Abstract: A symbol is a pattern (of physical marks, electromagnetic energy, etc.) which denotes, designates, or otherwise has meaning. The notion that intelligence requires the use and manipulation of symbols, and that humans are therefore symbol systems, has been extremely influential in artificial intelligence. The article has two parts. We begin with a presentation and discussion of the idea of a physical symbol system (PSS), as formulated by Newell and Simon. This notion, and the associated physical symbol system hypothesis (PSSH), were first presented--under somewhat different names--in (Newell and Simon 1972), with later fuller formulations (Newell and Simon 1976, Newell 1980) and still later elaborations (Newell 1990). The second part consists of a discussion of various objections to PSS/PSSH and replies, especially with reference to the themes of symbol grounding, situated cognition, embodiment, and situated robotics.

Representations of dialogue state for domain and task independent meta-dialogue. David Traum, Carl Andersen, Yuan Chong, Darsana Josyula, Michael O'Donovan-Anderson, Yoshi Okamoto, Khemdut Purang and Don Perlis. Electronic Transactions on AI 6, 2002.
  Abstract: We propose a representation of local dialog context motivated by the need to react appropriately to meta-dialogue, such as various sorts of corrections to the sequence of an instruction and response action. Such context includes at least the following aspects: the words and linguistic sturctures uttered, the domain correlates of those linguistic structures, and plans and actions in response. Each of these is needed as part of the context in order to be able to correctly interpret the range of possible corrections. Partitioning knowledge of dialog structure in this way may lead to an ability to represent dialog structure (e.g., in the form of axioms), which can be particularized to the domain, topic and content of the dialog.

The Big Lie: Some thoughts on liberal education. Michael O'Donovan-Anderson. Salon Magazine, January, 1999.
  Abstract: Why students don't respect their own education enough to resist cheating.

Wittgenstein and Rousseau on the context of justification. Michael O'Donovan-Anderson. Philosophy and Social Criticism 22(3):75-92, 1996.
  Abstract: The historical aim of this paper is to reveal some striking similarities in Wittgenstein's treatment of epistemic justification, and Rousseau's treatment of political justification. The theoretical aim is to open up the possibility of an understanding of justification which requires neither the discovery of some fundamental ground for judgment nor the alienation of the judge from the community or practice to be justified. Against the prevailing tradition in which justification occurs by reflectively rooting the practice in question in some unquestioned ground outside of and unaffected by that practice, a process that requires of the judge that her reason be untainted by practical involvements, both thinkers assert that justification can take place only within, being practically engaged with, whatever is to be justified. Indeed, we can go so far as to say for these thinkers that practical involvement is precisely the production of the grounds of legitimacy, and reasoned judgment is possible only from an engaged perspective.

 

Conference Proceedings

Quantifying the diversity of neural activations in individual brain. Anderson, M. L. & Pessoa, L. Proceedings of the 33rd Annual Conference of the Cognitive Science Society, 2011.
  Abstract: This paper offers the first comprehensive characterization of the cognitive diversity of individual brain regions. The results suggest that individual brain regions—even fairly small regions—contribute to multiple tasks across different cognitive-emotional domains, and moreover that there is little difference in diversity between cortical and sub-cortical circuits.

The Relation between Finger Gnosis and Mathematical Ability: Can we Attribute Function to Cortical Structure with Cross-Domain Modeling?. Marcie Penner-Wilger and Michael L. Anderson. Proceedings of the 33rd Annual Cognitive Science Society., 2011.
  Abstract: This paper details and applies a novel method for assigning function to local cortical structure. Imaging results from multiple cognitive domains were used to investigate what a shared neural substrate could be contributing to two apparently different domains: finger and number representation. We identified a region within the left precentral gyrus contributing to both tasks; identified, across several cognitive domains, other cognitive uses to which the ROI may have been put; and looked across these cognitive uses to ascertain the functional contribution of the ROI. The result of this process is a proposed local working—an array of pointers—that can be tested empirically and will allow for further elaboration of the redeployment view of the relation between finger and number representations. This work is significant for understanding the relationship between finger gnosis and math, and for introducing cross-domain modeling as a new empirical method.

Metacognition for Detecting and Resolving Conflicts in Operational Policies. Michael L. Anderson, Tim Oates, Matthew D. Schmill, Donald R. Perlis, Darsana P. Josyula, Bette Donahue, Matt McCaslin, and Michelle Snowden, Conference Proceedings of AAAI 2010.
  Abstract: Informational conflicts in operational policies cause agents to run into situations where responding based on the rules in one policy violates the same or another pol- icy. Static checking of these conflicts is infeasible and impractical in a dynamic environment. This paper dis- cusses a practical approach to handling policy conflicts in real-time domains within the context of a hierarchi- cal military command and control simulated system that consists of a central command, squad leaders and squad members. All the entities in the domain function according to pre- set communication and action protocols in order to per- form successful missions. Each entity in the domain is equipped with an instance of a metacognitive com- ponent to provide on-board/on-time analysis of actions and recommendations during the operation of the sys- tem. The metacognitive component is the Metacogni- tive Loop (MCL) which is a general purpose anomaly processor designed to function as a cross-domain plug- in system. It continuously monitors expectations and notices when they are violated, assesses the cause of the violation and guides the host system to an appropriate response. MCL makes use of three ontologies—indications, fail- ures and responses—to perform the notice, assess and guide phases when a conflict occurs. Conflicts in the set of rules (within a policy or between policies) manifest as expectation violations in the real world. These ex- pectation violations trigger nodes in the indication on- tology which, in turn, activate associated nodes in the failure ontology. The responding failure nodes then ac- tivate the appropriate nodes in the response ontology. Depending on which response node gets activated, the actual response may vary from ignoring the conflict to prioritizing, modifying or deleting one or more conflict- ing rules.

The Metacognitive Loop: An Architecture for Building Robust Intelligent Systems. H. Haidarian, W. Dinalankara, S. Fults, S. Wilson, Don Perlis, M. Schmill, T. Oates, D. P. Josyula, Michael L. Anderson, Proceedings of the AAAI Fall Symposium on Commonsense Knowledge , AAAI/CSK'10, Arlington, VA, USA, November 11-13, 2010
  Abstract: What commonsense knowledge do intelligent systems need, in order to recover from failures or deal with unexpected situations? It is impractical to represent predetermined solutions to deal with every unanticipated situation or provide predetermined fixes for all the different ways in which systems may fail. We contend that intelligent systems require only a finite set of anomaly-handling strategies to muddle through anomalous situations. We describe a generalized metacognition module that implements such a set of anomaly-handling strategies and that in principle can be attached to any host system to improve the robustness of that system. Several implemented studies are reported, that support our contention.

A critique of multi-voxel pattern analysis. Michael L. Anderson and Tim Oates. Proceedings of the 32nd Annual Conference of the Cognitive Science Society, 2010.
  Abstract: Multi-voxel pattern analysis (MVPA) is a popular analytical technique in neuroscience that involves identifying patterns in fMRI BOLD signal data that are predictive of task conditions. But the technique is also frequently used to make inferences about the regions of the brain that are most important to the tasks in question, and our analysis shows that this is a mistake. MVPA does not provide a reliable guide to what information is being used by the brain during cognitive tasks, nor where that information is. This is due in part to inherent run to run variability in the decision space generated by the classifier, but there are also several other issues, discussed below, that make inference from the characteristics of the learned models to relevant brain activity deeply problematic. These issues have significant implications both for many papers already published, and for how the field uses this technique in the future.

The origins of collective overvaluation: Irrational exuberance emerges from simple, honest and rational individual behavior. Michael L. Anderson and C. Athena Aktipis. Proceedings of the 32nd Annual Conference of the Cognitive Science Society, 2010.
  Abstract: The generation of value bubbles is an inherently psychological and social process, where information sharing and individual decisions can affect representations of value. Bubbles occur in many domains, from the stock market, to the runway, to the laboratories of science. Here we seek to understand how psychological and social processes lead representations (i.e., expectations) of value to become divorced from the inherent value, using asset bubbles as an example. We hypothesize that simple asset group switching rules can give rise to aggregate behavior that resembles the irrational exuberance that can drive asset bubbles. Using an agent-based model we explore whether a simple switching rule can generate irrational exuberance, and systematically explore how communication between decision makers influences the speed and intensity of overvaluation. We show that rational and simple individual level rules combined with honest information sharing are sufficient to generate the collective overvaluation characteristic of irrational exuberance. Further, our results demonstrate that low fidelity in the exchange of value information leads to rapidly increasing expectations about value, even when no one is engaged in exaggerating their expectations for the assets they own.

An alternative view of the relation between finger and math ability: Redeployment of finger representations for the representation of number. Marcie Penner-Wilger and Michael L. Anderson. Proceedings of the 30th Annual Conference of the Cognitive Science Society, 2008.
  Abstract: This paper elaborates a novel hypothesis regarding the observed predictive relation between finger gnosis and mathematical ability. In brief, we suggest that these two cognitive phenomena have overlapping neural substrates, as the result of the re-use ("redeployment") of part of the finger gnosis circuit for the purpose of representing number. We offer some background on the relation and current explanations for it; an outline of our alternate hypothesis; some evidence supporting redeployment over current views; and a plan for further research.

Do redeployed finger representations underlie math ability?. Michael L. Anderson, Marcie Penner-Wilger. Member Poster, Proceedings of the 29th Annual Conference of the Cognitive Science Society, 2007.
  Abstract: Finger gnosia is the ability to distinguish, without visual feedback, which fingers have been lightly touched. Developmentally, finger gnosia has been found to predict children’s mathematics performance (for a review see Penner-Wilger et al., 2007). The question of why finger gnosia and math are related is an issue of debate. 
Our purpose in this poster is to (1) outline a novel hypothesis explaining the observed correlation, (2) point out some evidence in support of the hypothesis, and (3) suggest some further empirical predictions of the hypothesis.

Massive redeployment and the evolution of cognition. Michael L. Anderson. Publication-based talk, Proceedings of the 29th Annual Conference of the Cognitive Science Society, 2007.
  Abstract: The creative re-use of existing neural components may have played a significant role in the evolutionary development of cognition. There are obvious evolutionary advantages to such redeployment, and the data presented here confirm three important empirical predictions of this account of the development of cognition: (1) a typical brain area will be utilized by many cognitive functions in diverse task categories, (2) evolutionarily older brain areas will be deployed in more cognitive functions and (3) more recent cognitive functions will utilize more, and more widely scattered brain areas. These findings have implications not just for our understanding of the evolutionary origins of cognitive function, but also for the practice of both clinical and experimental neuroscience.

Evidence for massive redeployment of brain areas in cognitive functions. Michael L. Anderson. Proceedings of the 28th Annual Conference of the Cognitive Science Society, 2006.
  Abstract: This essay discusses evidence for the massive redeployment hypothesis, an account of the functional organization of the brain that centrally features the fact that brain areas are typically employed to support numerous functions. The massive redeployment hypothesis is supported by case studies of redeployment, as well as an empirical review of 135 brain imaging experiments.

ReGiKAT: (Meta-)Reason-Guided Knowledge Acquisition and Transfer (, Michael L. Anderson, Tim Oates, and Don Perlis Proceedings of the 11th International on Information Processing and management of Uncertainty in Knowledge-Based Systems, 2006.
  Abstract: We propose a methodology for the design and implementation of systems that will learn to succeed where in the past they have failed. Such systems will know what they are supposed to be doing, know when they are succeeding and when they are not, and be able to make targeted changes to their own modules to correct their failures. That is, they will be self-monitoring, self-correcting, and self-guided learning-and-reasoning systems, advanced active learners able to decide what, when, and how to learn. We also describe some of our pilot studies utilizing this methodology.

On the types, frequency, uses and characteristics of meta-language in conversation. Michael L. Anderson, Bryant Lee, Jon Go, Shuda Li, Ben Sutandio and LuoYan Zhou. Proceedings of the 28th Annual Conference of the Cognitive Science Society, 2006.
  Abstract: Human dialog is a highly collaborative and interactive process, that includes the ability to talk about the dialog itself and its linguistic constituents, and to use meta-linguistic interactions to help coordinate the ongoing conversation. However, very little is known about the frequency and conditions under which people resort to meta-language, its range of uses, and any characteristics that may be useful to its automated identification. This paper presents the results of a corpus study in which a markup scheme for meta-language was applied to a sub-set of the British National Corpus. The corpus study made it possible to demonstrate that sentences containing meta-language show a high degree of correlation with instances of dialog management, and that automated detection of meta-language should be feasible, based on word-frequency analysis.

On the reasoning of real-world agents: Toward a semantics for active logic. Michael L. Anderson Walid Gomaa, John Grant and Don Perlis. Proceedings of the 7th Annual Symposium on the Logical Formalization of Commonsense Reasoning, Dresden University Technical Report (ISSN 1430-211X), 2005.
  Abstract: For some time we have been developing, and have had significant practical success with, a time-sensitive, contradiction-tolerant logical reasoning engine called active logic. The current paper details a restricted semantics for active logic. Central to active logic are special rules controlling the inheritance of beliefs in general, and beliefs about the current time in particular, very tight controls on what can be derived from direct contradictions (P & -P), and mechanisms allowing an agent to represent and reason about its own beliefs and past reasoning. Furthermore, inspired by the notion that until an agent notices that a set of beliefs is contradictory, that set seems consistent (and the agent therefore reasons with it as if it were consistent), we introduce a "perception function'' that represents an agent's limited awareness of (the consequences of) its own beliefs, and serves to modify inconsistent belief sets so as to yield consistent sets. Based on these ideas, this paper introduces a new definition of model and of logical consequence, as well as a new definition of soundness such that, when reasoning with consistent premises, all classically sound rules are sound for active logic. However, not everything that is classically sound remains sound in our sense, for by classical definitions, all rules with contradictory premises are vacuously sound, whereas in active logic not everything follows from a contradiction.

Metacognition for dropping and reconsidering intentions. Darsana Josyula, Michael L. Anderson, and Don Perlis. Proceedings of the AAAI Spring Symposium on Metacognition in Computation, 2005.
  Abstract: In this paper, we present an approach for dropping and reconsidering intentions, wherein concurrent actions and results are allowed, in the framework of the time-sensitive and contradiction-tolerant active logic. In this approach, a metacognitive process strives to dynamically mark intentions as achievable, unachievable or achieved, drop futile or achieved intentions and create alternative intentions for currently unachievable intentions when possible. Since, this process runs concurrently (and shares resources) with the cognitive activities of the agent, the amount of resources available for the process depends on real-time conditions. Therefore, when and whether intentions are dropped or reconsidered depends on the conditions and resources available at run-time.

A brief introduction to the guidance theory of representation. Gregg Rosenberg and Michael L. Anderson. Proceedings of the 26th Annual Conference of the Cognitive Science Society, 2004.
  Abstract: Recent trends in the philosophy of mind and cognitive science can be fruitfully characterized as part of the ongoing attempt to come to grips with the very idea of homo sapiens--an intelligent, evolved, biological agent--and its signature contribution is the emergence of a philosophical anthropology which, contra Descartes and his thinking thing, instead puts doing at the center of human being. Applying this agency-oriented line of thinking to the problem of representation, this paper introduces the Guidance Theory, according to which the content and intentionality of representations can be accounted for in terms of the way they provide guidance for action. We offer a brief account of the motivation for the theory, and a formal characterization.
Domain-Independent Reason-Enhance Controller for Task-ORiented systems - DIRECTOR. () Darsana P. Josyula, Michael L. Anderson and Don Perlis, Proceedings of AAAI 2004
  Abstract: In today’s market, different systems (e.g., camera, mi- crowave etc.) exist that can perform specialized tasks. How- ever, users find it frustrating to learn how to operate these task-oriented systems (TOSs) in a manner that suits their needs. If a single agent can interface users with different TOSs, then the users need not learn how to interact with each TOS separately; instead, they just need to learn how to interact with one agent. In addition, if the agent is ratio- nal, users can flexibly adapt the operation of the TOSs by interacting with the agent. For example, consider a pool controller that can accept commands to heat a pool, stop heating, and provide the tem- perature. A user interacting directly with such a system will have to issue the appropriate commands when required. By integrating a rational interfacing agent with such a system, the user could tell the agent to heat the pool every Saturday at 10:00 am and maintain the temperature around 35oC until 1:00 pm. The agent will then issue appropriate commands to the pool controller at the required times. For such an interfacing agent to effectively control differ- ent TOSs it should have the capability not only to translate a user request into a TOS instruction, and to issue that in- struction to the TOS at the appropriate time(s), but also to track the effect of those commands and to detect any pertur- bations, such as contradictory information, or a difference between expected and actual outcomes. We are developing such a perturbation tolerant, domain- independent interfacing agent (Anderson, Josyula, & Perlis 2003; Josyula, Anderson, & Perlis 2003) by modeling the beliefs, desires, intentions, expectations and achievements of the agent. The current version of the agent has been suc- cessfully integrated with and tested on six different TOSs. Our agent is built on a logical engine (ALFA - Active Logic For Agents) based on Active Logic (Elgot-Drapkin & Perlis 1990; Purang et al. 1999; Purang 2001). ALFA can keep track of the evolving time, handle contradictory infor- mation and distinguish between desires, intentions and ex- pectations that are achievable and those that are not. There- fore, our agent based on ALFA can rationally deliberate despite having deadlines and contradictory beliefs, desires or other mental attitudes. In addition, it can allocate its resources to satisfy achievable goals, resist attempting un-achievable goals (until they become achievable) and ignore achieved goals.

Specification of a test environment and performance measures for perturbation-tolerant cognitive agents. Michael L. Anderson. Proceedings of the AAAI Workshop on Intelligent Agent Architectures, 2004.
  Abstract: In this paper I propose a flexible method of characterizing a test environment such that its environmental complexity, information density, variability and volatility can be easily measured. This allows one to determine the task performance of a cognitive agent as a function of such measures, and therefore permits derivative measures of the perturbation tolerance of cognitive agents--that is, their ability to cope with a complex and changing environment.

Active Logic for more effective human-computer interaction and other commonsense applications. Michael L. Anderson, Darsana Josyula, Khemdut Purang and Don Perlis. Proceedings of the International Joint Conference on Automated Reasoning, Workshop on Empirically Successful First Order Reasoning, 2004.
  Abstract: The demands of real-time commonsense reasoning---as evidenced for example in the pragmatics of human-computer dialog---put stringent requirements on the underlying logic, including those of (i) perturbation tolerance, (ii) contradiction tolerance and (iii) time situatedness. Active logic is an attempt to meet all of these needs. In this paper we present this work and its application to natural language dialog via time-sensitive meta-reasoning. We illustrate this with a description of ALFRED, a cooperative natural language interface to multiple task-oriented domains.

Empirical results for the use of meta-language in dialog management.. Michael L. Anderson and Bryant Lee. Member Poster, Proceedings of the 26th Annual Conference of the Cognitive Science Society, 2004
  Abstract: As is well known, dialog partners manage the uncertainty inherent in conversation by continually providing and eliciting feedback, monitoring their own comprehension and the apparent comprehension of their dialog partner, and initiating repairs as needed. Given the nature of such monitoring and repair, one might reasonably hypothesize that a good portion of the utterances involved in dialog management employ meta-language. But while there has been a great deal of work on the specific topic of dialog management, and it is widely (if often tacitly) accepted that meta-language is frequently involved, there has been no work specifically investigating and quantifying the role of meta-language in dialog management. Thus, this small study investigated the correlation between meta-language and dialog management utterances in three dialog files of the British National Corpus (BNC).

Prelinguistic agents will form only egocentric representations.Michael L. Anderson and Tim Oates. Commentary on Hurford: The neural basis of predicate-argument structure, 2003.

  Abstract: The representations formed by the ventral and dorsal streams of a prelinguistic agent will tend to be too qualitatively similar to support the distinct roles required by PREDICATE(x) structure. We suggest that the attachment of qualities to objects is not a product of the combination of these separate processing streams, but is instead a part of the process- ing required in each. In addition, we suggest that the formation of objective predicates is inextricably bound up with the emergence of language itself, and so cannot be cleanly identified with any prelinguistic cognitive capacities.

Talking to Computers. Michael L. Anderson, Darsana Josyula and Don Perlis. Proceedings of the Workshop on Mixed Initiative Intelligent Systems, IJCAI-2003.

  Abstract: Our broad claim is that time-sensitive metareasoning can enhance the ability of natural language HCI systems to converse with human interlocutors, by giving these systems both the time-awareness and meta-linguistic skills (including especially the ability to recognize and repair dialog problems, by learning if need be) which appear to be necessary for free, flexible, and natural conversation. We illustrate this enhancement with a desciption of our ongoing work in cooperative natural language HCI systems.

Toward task-oriented, domain independent conversational adequacy. Darsana Josyula, Michael L. Anderson and Don Perlis. Intelligent System Demonstrations, Proceedings of IJCAI, 2003.

  Abstract: A description of ALFRED, our natural-language HCI system, which can use and understand meta-language, and acts as an interface between the user and a task-oriented system, providing a bed for dialog correction and repair.

Time Situated Agency: Active Logic and Intention Formation. Michael L. Anderson, Darsana Josyula, Yoshi Okamoto, and Don Perlis. Proceedings of the Cognitive Agents Workshop, German Conference on Artificial Intelligence, 2002.

  Abstract: In recent years, embodied cognitive agents have become a central research focus in Cognitive Science. We suggest that there are at least three aspects of embodiment---physical, social and temporal---which must be treated simultaneously to make possible a realistic implementation of agency. In this paper we detail the ways in which attention to the temporal embodiment of a cognitive agent (perhaps the most neglected aspect of embodiment) can enhance the ability of an agent to act in the world, both in itself, and also by supporting more robust integrations with the physical and social world.

The Use-Mention Distinction and its Importance to HCI. Michael L. Anderson, Yoshi Okamoto, Darsana Josyula, and Don Perlis. Proceedings of EDILOG: Sixth Workshop on the Semantics and Pragmatics of Dialog, 2002.

  Abstract: In this paper we contend that the ability to engage in meta-dialog is necessary for free and flexible conversation. Central to the possibility of meta-dialog is the ability to recognize and negaotiate the distinction between the use and mention of a word. The paper surveys existing theoretical approaches to the use-mention distinction, and briefly describes some of our ongoing efforts to implement a system which represents the use-mention distinction in the service of simple meta-dialog.

Seven Days in the Life of a Robotic Agent. Waiyian Chong, Michael O'Donovan-Anderson, Yoshi Okamoto and Don Perlis. Proceedings of the GSFC/JPL Workshop on Radical Agent Concepts, 2002.
  Abstract: Bootstrapping is a widely employed technique in the process of building highly complex systems such as microprocessors, language compilers, and computer operating systems. It could play an even more prominent role in the creation of computation systems capable of supporting intelligent agent behaviors because of the even higher level of complexity. The prospect of a self-bootstrapping, self-improving intelligent system has motivated various fields of research in machine learning. However, a robust, generalizable methodology of machine learning is yet to be found; there are still a lot of learning behaviors that no existing learning techniqueer and flexibility (but is slow) and the latter is very fast but hard to adapt to new situations. We will explore the possibilities of using reflection and continual computation towards this end.

Handling Uncertainty with Active Logic. M. Anderson, M. Bhatia, P. Chi, W. Chong, D. Josyula, Y. Okamoto, D. Perlis and K. Purang. Proceedings of the AAAI Fall Symposium, 2001
  Abstract: Reasoning in a complex and dynamic world requires considerable flexibility on the part of the reasoner; flexibility to apply -- in the right circumstances -- the right tools (e.g. probabilities, defaults, metareasoning, belief revision, contradiction-resolution, and so on). A formalism that has been developed with this purpose in mind is that of active logic. Active logic is combines inference rules with a constantly evolving measure of time (a 'now') that itself can be referenced in those rules.

 

Book Reviews

A review of How the body shapes the way we think: A new view of intelligence., by Rolf Pfeifer and Josh Bongard. Artificial Intelligence 174: 152-4, 2010.

A review of Neuroeconomics: Decision making and the brain., by Paul Glimcher, Colin F. Camerer, Ernst Fehr and Russell A. Poldrack, eds. Journal of Economic Psychology 31: 151-4, 2010.

A review of Second Nature: Brain Science and Human Knowledge, by Gerald Edelman Teachers College Record, 2008.

Embodied cognition: the teenage years. A review of How the Body Shapes the Mind, by Shaun Gallagher. Philosophical Psychology, 20(1): 127-31, 2007.

Strike while the iron is. A review of Reconstructing the Cognitive World, by Michael Wheeler. Artificial Intelligence 170(18): 1213-17, 2006.

Why is AI so scary? (Multiple book review essay) Artificial Intelligence 169(2): 201-8, 2005.
The #2 most downloaded article from Artificial Intelligence for Q4 2005; top 15 for 2006!

Evan's Varieties of Reference and the Anchoring Problem, Robotics and Autonomous Systems Journal 43(2-3): 189-92, 2003.

Philosophy in the Flesh, by George Lakoff and Mark Johnson The Review of Metaphysics, June 2000.

Socratic Puzzles, by Robert Nozick The Review of Metaphysics, June 1999.

God and the Natural World: Religion and Science in Antebellum America, by Walter H. Conser, Jr. The Journal of the History of Medicine, June 1995.

Genius and Talent, by David A Weiner The Philosopher, April 1994.

Wittgenstein on Words as Instruments, by J.F.M. Hunter The Philosopher, April 1993.

 

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