Craik published only one complete work of any length, this essay on The Nature of Explanation.

Continuing his exploration of the organization of complexity and the science of design, this new edition of Herbert Simon's classic work on artificial ...

Although work on computational and robotic modelling of cognition is highly diverse, as an empirical method it can be roughly divided into at least two clearly different, though non-exclusive branches, motivated to evaluate the sufficiency or the necessity of theories when it comes to accounting for data and/or other observations. With the rising profile of theories of situated/embodied cognition, a third non-exclusive avenue for investigation has also gained in popularity, the investigation of agent-environment embedding or more generally, exploration. Still in (...) its infancy, and often confused with sufficiency testing, this relatively new kind of modelling, which is theory- rather than data-driven, investigates the role of the environment in shaping the ontogenetic and/or phylogenetic development of situated agency. Each of these three approaches presents many issues that modellers must be sensitive to, both in the design of experiments, and in the conclusions that can be drawn from them. This paper highlights some of these issues, provides examples, and addresses the contribution of computational/robotic modelling to cognitive science, as well as some of its limitations. (shrink)

In this article we will argue that given certain conditions for the evolution of bi- ological controllers, these will necessarily evolve in the direction of incorporating consciousness capabilities. We will also see what are the necessary mechanics for the provision of these capabilities and extrapolate this vision to the world of artifi- cial systems postulating seven design principles for conscious systems. This article was published in the journal Neural Networks special issue on brain and conscious- ness.

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.

This paper proposes a brain-inspired cognitive architecture that incorporates approximations to the concepts of consciousness, imagination, and emotion. To emulate the empirically established cognitive efficacy of conscious as opposed to non-conscious information processing in the mammalian brain, the architecture adopts a model of information flow from global workspace theory. Cognitive functions such as anticipation and planning are realised through internal simulation of interaction with the environment. Action selection, in both actual and internally simulated interaction with the environment, is mediated by (...) affect. An implementation of the architecture is described which is based on weightless neurons and is used to control a simulated robot. (shrink)

Can we make progress exploring consciousness? Or is it forever beyond human reach? In science we never know the ultimate outcome of the journey. We can only take whatever steps our current knowledge affords. This paper explores today's evidence from the viewpoint of Global Workspace theory. First, we ask what kind of evidence has the most direct bearing on the question. The answer given here is ‘contrastive analysis’ -- a set of paired comparisons between similar conscious and unconscious processes. This (...) body of evidence is already quite large, and constrains any possible theory . Because it involves both conscious and unconscious events, it deals directly with our own subjective experience, as anyone can tell by trying the demonstrations in this article. (shrink)

In this collection of essays we hear from an international array of computer and brain scientists who are actively working from both the machine and human ends...

This book presents an attempt to develop a theory of knowledge and a philosophy of mind using ideas derived from the mathematical theory of communication developed by Claude Shannon. Information is seen as an objective commodity defined by the dependency relations between distinct events. Knowledge is then analyzed as information caused belief. Perception is the delivery of information in analog form for conceptual utilization by cognitive mechanisms. The final chapters attempt to develop a theory of meaning by viewing meaning as (...) a certain kind of information-carrying role. (shrink)

In this book, Newell makes the case for unified theories by setting forth a candidate.

This essay is a sustained attempt to bring new light to some of the perennial problems in philosophy of mind surrounding phenomenal consciousness and introspection through developing an account of sensory and phenomenal concepts. Building on the information-theoretic framework of Dretske (1981), we present an informational psychosemantics as it applies to what we call sensory concepts, concepts that apply, roughly, to so-called secondary qualities of objects. We show that these concepts have a special informational character and semantic structure that closely (...) tie them to the brain states realizing conscious qualitative experiences. We then develop an account of introspection which exploits this special nature of sensory concepts. The result is a new class of concepts, which, following recent terminology, we call phenomenal concepts: these concepts refer to phenomenal experience itself and are the vehicles used in introspection. On our account, the connection between sensory and phenomenal concepts is very tight: it consists in different semantic uses of the same cognitive structures underlying the sensory concepts, such as the concept of red. Contrary to widespread opinion, we show that information theory contains all the resources to satisfy internalist intuitions about phenomenal consciousness, while not offending externalist ones. A consequence of this account is that it explains and predicts the so-called conceivability arguments against physicalism on the basis of the special nature of sensory and phenomenal concepts. Thus we not only show why physicalism is not threatened by such arguments, but also demonstrate its strength in virtue of its ability to predict and explain away such arguments in a principled way. However, we take the main contribution of this work to be what it provides in addition to a response to those conceivability arguments, namely, a substantive account of the interface between sensory and conceptual systems and the mechanisms of introspection as based on the special nature of the information flow between them. (shrink)

The study of creative, diagnostic, visual, spatial, analogical, and temporal reasoning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of traditional notions of reasoning such as classical logic. Understanding the contribution of modeling practices to discovery and conceptual change in science requires expanding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. The study of these heuristic (...) ways of reasoning is situated at the crossroads of philosophy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model-based reasoning. The term "model" comprises both internal and external representations. The models are intended as interpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain. Moreover, in the modeling process, various forms of abstraction are used. Evaluation and adaptation take place in light of structural, causal, and/or functional constraints. Model simulation can be used to produce new states and enable evaluation of behaviors and other factors. Several of the papers in this volume aim at increasing epistemological knowledge about the role of model-based reasoning in various scientific tasks, other papers address fundamental cognitive issues related to model-based reasoning and illustrate novel analyses of cognitive "logical" models of model-based reasoning and of the interplay abduction/model-based reasoning/creative inferences. The volume is based on the papers that were presented at the International Conference Model-Based Reasoning in Science and Engineering: Abduction, Visualization, Simulation, held at the Collegio Ghislieri, University of Pavia, Pavia, Italy, in December 2004. (shrink)

Although work on computational and robotic modelling of cognition is highly diverse, as an empirical method it can be roughly divided into at least two clearly different, though non-exclusive branches, motivated to evaluate the sufficiency or the necessity of theories when it comes to accounting for data and/or other observations. With the rising profile of theories of situated/embodied cognition, a third non-exclusive avenue for investigation has also gained in popularity, the investigation of agent-environment embedding or more generally, exploration. Still in (...) its infancy, and often confused with sufficiency testing, this relatively new kind of modelling, which is theory- rather than data-driven, investigates the role of the environment in shaping the ontogenetic and/or phylogenetic development of situated agency. Each of these three approaches presents many issues that modellers must be sensitive to, both in the design of experiments, and in the conclusions that can be drawn from them. This paper highlights some of these issues, provides examples, and addresses the contribution of computational/robotic modelling to cognitive science, as well as some of its limitations. (shrink)

This paper extends three decades of work arguing that researchers who discuss consciousness should not restrict themselves only to (adult) human minds, but should study (and attempt to model) many kinds of minds, natural and artificial, thereby contributing to our understanding of the space containing all of them. We need to study what they do or can do, how they can do it, and how the natural ones can be emulated in synthetic minds. That requires: (a) understanding sets of requirements (...) that are met by different sorts of minds, i.e. the niches that they occupy, (b) understanding the space of possible designs, and (c) understanding complex and varied relationships between requirements and designs. Attempts to model or explain any particular phenomenon, such as vision, emotion, learning, language use, or consciousness lead to muddle and confusion unless they are placed in that broader context. A methodology for making progress is summarised and a novel requirement proposed for a theory of how human minds work: the theory should support a single generic design for a learning, developing system that, in addition to meeting familiar requirements, should be capable of developing different and opposed philosophical viewpoints about consciousness, and the so-called hard problem. In other words, we need a common explanation for the mental machinations of mysterians, materialists, functionalists, identity theorists, and those who regard all such theories as attempting to answer incoherent questions. No designs proposed so far come close. (shrink)

I consider the role of cognitive modeling in cognitive science. Modeling, and the computers that enable it, are central to the field, but the role of modeling is often misunderstood. Models are not intended to capture fully the processes they attempt to elucidate. Rather, they are explorations of ideas about the nature of cognitive processes. In these explorations, simplification is essential—through simplification, the implications of the central ideas become more transparent. This is not to say that simplification has no downsides; (...) it does, and these are discussed. I then consider several contemporary frameworks for cognitive modeling, stressing the idea that each framework is useful in its own particular ways. Increases in computer power (by a factor of about 4 million) since 1958 have enabled new modeling paradigms to emerge, but these also depend on new ways of thinking. Will new paradigms emerge again with the next 1,000‐fold increase? (shrink)

In this volume the author tackles this problem in a rigorous analysis which begins with the general dynamics of living systems and leads the reader step-by-step ...