Michael Anderson

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

In this essay we respond to some criticisms of the guidance theory of representation offered by Tom Roberts. We argue that although Roberts’ 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

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, selfconfiguring, 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, robust AI systems.

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.

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 metacognitive 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 article 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.

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 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 representation of fictional and abstract entities. Being both representational and actiongrounded, the guidance theory may provide some common ground between embodied and cognitivist approaches to the study of the mind

At the turn of the 21st century, Susan Leigh Anderson and Michael Anderson conceived and introduced the Machine Ethics research program, that aimed to highlight the requirements under which autonomous artificial intelligence systems could demonstrate ethical behavior guided by moral values, and at the same time to show that these values, as well as ethics in general, can be representable and computable. Today, the interaction between humans and AI entities is already part of our everyday lives; in the near future it is expected to play a key role in scientific research, medical practice, public administration, education and other fields of civic life. In view of this, the debate over the ethical behavior of machines is more crucial than ever and the search for answers, directions and regulations is imperative at an academic, institutional as well as at a technical level. Our discussion with the two inspirers and originators of Machine Ethics highlights the epistemological, metaphysical and ethical questions arising by this project, as well as the realistic and pragmatic demands that dominate artificial intelligence and robotics research programs. Most of all, however, it sheds light upon the contribution of Susan and Michael Anderson regarding the introduction and undertaking of a main objective related to the creation of ethical autonomous agents, that will not be based on the “imperfect” patterns of human behavior, or on preloaded hierarchical laws and human-centric values.

Embodied Cognition is growing up, and How the Body Shapes the Mind is both a sign of, and substantive contributor to this ongoing development. Born in or about 1991, EC is only now emerging from a tumultuous but exciting childhood marked in particular by the size and breadth of the extended family hoping to have some impact on its early education and upbringing. As family members include computer science, phenomenology, developmental and cognitive psychology, analytic philosophy of mind, linguistics, neuroscience, and eastern mysticism, just to name a few, EC has both benefited and suffered from a wealth of different and often incompatible ideas about who and what it is, what it should do with its life, even what language it should speak. Gallagher brings some cohesion and consistency to this situation, not by surveying and synthesizing these competing approaches, but by focusing on some fundamental issues, and carefully marshalling the evidence and developing the vocabulary to thoroughly consider them.

Part of understanding the functional organization of the brain is understanding how it evolved. This talk presents evidence suggesting that while the brain may have originally emerged as an organ with functionally dedicated regions, the creative re-use of these regions has played a significant role in its evolutionary development. This would parallel the evolution of other capabilities wherein existing structures, evolved for other purposes, are re-used and built upon in the course of continuing evolutionary development (“exaptation”: Gould & Vrba 1982). There is psychological support for exaptation in cognition (e.g. Cosmides 1989), theoretical reason to expect it (Anderson 2003; in press-a; in press-b) and neuroanatomic evidence that the brain evolved by preserving, extending, and combining existing network components, rather than by generating complex structures de novo (Sporns & Kötter 2004). However, there has been little evidence that integrates these perspectives, bringing such an account of the evolution of cognitive function into the realm of cognitive neuroscience (although see, e.g., Barsalou 1999).

The current paper details a restricted semantics for active logic, a time-sensitive, contradictiontolerant logical reasoning formalism. 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. Using these ideas, we introduce 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.

For the least the last 10 years, there has been growing interest in, and grow- ing evidence for, the intimate relations between more abstract or higher order cognition—such as reasoning, planning, and language use—and the more con- crete, immediate, or lower order operations of the perceptual and motor sys- tems that support seeing, feeling, moving, and manipulating. A sub-field of the larger research program in embodied cognition (Clark, 1997, 1998; Wilson, 2001; Anderson, 2003, 2007d, 2008; Gibbs, 2006), this work has generally pro- ceeded under the banner of grounded cognition, and works to support the claim that thinking is inherently tied to—grounded in—perceiving and acting. Thus, Glenberg and Kaschak (2002) discuss “grounding language in action”; Gallese and Lakoff (2005) argue that concepts are “grounded in the sensory–motor sys- tem;” and Barsalou (1999) at various times talks of “grounding cognition in perception,” “grounding conceptual knowledge in modality-specific systems” (Barsalou et al., 2003), and most recently simply of “grounded cognition” (Barsalou, 2008).

As part of the ongoing attempt to fully naturalize the concept of human being--and, more specifically, to re-center it around the notion of agency--this essay discusses an approach to defining the content of representations in terms ultimately derived from their central, evolved function of providing guidance for action. This 'guidance theory' of representation is discussed in the context of, and evaluated with respect to, two other biologically inspired theories of representation: Dan Lloyd's dialectical theory of representation and Ruth Millikan's biosemantics.

Embodied cognition (EC) is growing up, and How the Body Shapes the Mind is both a sign of, and substantive contributor to, this ongoing development. Born in or about 1991 (the year of publication of seminal works by Brooks, Dreyfus, and Varela, Thompson & Rosch), EC is only now emerging from a tumultuous but exciting childhood marked in particular by the size and breadth of the extended family hoping to have some impact on its early education and upbringing. As family members include computer science, phenomenology, developmental and cognitive psychology, analytic philosophy of mind, linguistics, neuroscience, and eastern mysticism—just to name a few—EC has both benefited and suffered from a wealth of different and often incompatible ideas about who and what it is, what it should do with its life, even what language it should speak. Gallagher brings some cohesion and consistency to this situation, not by surveying and synthesizing these competing approaches, but by carefully marshalling the evidence and developing the vocabulary to thoroughly consider a few fundamental issues.

Description: The massive redeployment hypothesis (MRH) is a theory about the functional organization of the human cortex, 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.

In this paper, I summarize an emerging debate in the cognitive sciences over the right taxonomy for understanding cognition – the right theory of and vocabulary for describing the structure of the mind – and the proper role of neuroscientific evidence in specifying this taxonomy. In part because the discussion clearly entails a deep reconsideration of the supposed autonomy of psychology from neuroscience, this is a debate in which philosophers should be interested, with which they should be familiar, and to which they should contribute. Here, I outline some of the positions being advocated, and reflect on some of the possible implications of this work both for scientific and folk psychology.