The claim that similarity plays a role in representation has been philosophically discredited. Psychologists, however, routinely analyse the success of mental representations for guiding behaviour in terms of a similarity between representation and the world. I provide a foundation for this practice by developing a philosophically responsible account of the relationship between similarity and representation in natural systems. I analyse similarity in terms of the existence of a suitable homomorphism between two structures. The key insight is that by restricting attention (...) to only those homomorphisms induced by causal processes, we can solve two philosophical problems with a single assumption. First, causal structure provides an adequate source for the bias required to ensure the similarity relation is non-trivial; second, it provides an adequate source for the directionality required to move from similarity to representation. I defend this account against objections by Goodman and van Fraassen and demonstrate that it is indeed the account of similarity’s role in representation assumed by psychological practice. (shrink)

This is a bibliography of books and articles on consciousness in philosophy, cognitive science, and neuroscience over the last 30 years. There are three main sections, devoted to monographs, edited collections of papers, and articles. The first two of these sections are each divided into three subsections containing books in each of the main areas of research. The third section is divided into 12 subsections, with 10 subject headings for philosophical articles along with two additional subsections for articles in cognitive (...) science and neuroscience. Of course the division is somewhat arbitrary, but I hope that it makes the bibliography easier to use. This bibliography has first been compiled by Thomas Metzinger and David Chalmers to appear in print in two philosophical anthologies on conscious experience . From 1995 onwards it has been continuously updated by Thomas Metzinger, and now is freely available as a PDF-, RTF-, or HTML-file. This bibliography mainly attempts to cover the Anglo-Saxon and German debates, in a non-annotated, fully formatted way that makes it easy to "cut and paste" from the original file. To a certain degree this bibliography also contains items in other languages than English and German - all submissions in other languages are welcome. Last update of current version: July 13th, 2001. (shrink)

To understand the work of economic theorists it is often helpful to situate it in the context of the rhetorical strategy they were pursuing. Two ontologically distinct rhetorical strategies of laissez-faire may be distinguished by the way they articulate the individual interest with the general interest. A reductionist approach, exemplified by Friedman and Lucas, suggests that the properties and behaviour of an entity can be understood in terms of the properties and behaviour of the constituent lower-level components, taken in isolation. (...) The contrary – holistic – stance, viewing the qualities of phenomena as products of the inter-relations between their component parts, is characteristic of Smith and Hayek. While the reductionist approach naturally issues in a laissez- faire policy prescription, the holistic account is more problematic. Reconciling a holistic ontology with a reductionist policy prescription requires the intercalation of a black box, such as an evolutionary process or the invisible hand of a deity. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

For an artificial agent to be morally praiseworthy, its rules for behaviour and the mechanisms for supplying those rules must not be supplied entirely by external humans. Such systems are a substantial departure from current technologies and theory, and are a low prospect. With foreseeable technologies, an artificial agent will carry zero responsibility for its behavior and humans will retain full responsibility.

The ArgumentTheorists of science and culture, seeking to explicate the implications of chaos theory, quantum mechanics, or special and general relativity, have drawn parallels to the constellation of intellectual and social phenomena collected in the concept of postmodernism. The notion thereby invoked of a postmodern physics is suggestive and worth exploring. But it remains ungrounded so long as the argument moves in the realm of parallels. Moreover, these discussions prove to be tacitly constrained by a preexisting genre of physicists' own (...) literary production, a genre whose argumentative structures have been taken over implicitly into the subsequent exchanges. Attending critically in this way to the intellectual interests of the discussants — asking who it is that wants to constitute a postmodern physics — should open up more productive ways of framing the debate. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models.Higher-level analyses of these connectionist models reveal subtle relations to symbolic models. Parallel connectionist memory and linguistic processes are hypothesized to give rise to processes that are describable at a higher level as sequential rule application. At the lower level, computation has the character of massively parallel satisfaction of soft numerical constraints; at the higher level, this can lead to competence characterizable by hard rules. Performance will typically deviate from this competence since behavior is achieved not by interpreting hard rules but by satisfying soft constraints. The result is a picture in which traditional and connectionist theoretical constructs collaborate intimately to provide an understanding of cognition. (shrink)

We have learned that the issues we raised are very difficult to think about clearly, and what "works" for one thinker falls flat for another, and leads yet another astray. So it is particularly useful to get these re-expressions of points we have tried to make. Both commentaries help by proposing further details for the Multiple Drafts Model, and asking good questions. They either directly clarify, or force us to clarify, our own account. They also both demonstrate how hard it (...) is for even sympathetic commentators always to avoid the very habits of thought the Multiple Drafts Model was designed to combat. While acknowledging and expanding on their positive contributions, we must sound a few relatively minor alarms. (shrink)

A set of hypotheses is formulated for a connectionist approach to cognitive modeling. These hypotheses are shown to be incompatible with the hypotheses underlying traditional cognitive models. The connectionist models considered are massively parallel numerical computational systems that are a kind of continuous dynamical system. The numerical variables in the system correspond semantically to fine-grained features below the level of the concepts consciously used to describe the task domain. The level of analysis is intermediate between those of symbolic cognitive models (...) and neural models. The explanations of behavior provided are like those traditional in the physical sciences, unlike the explanations provided by symbolic models. Higher-level analyses of these connectionist models reveal subtle relations to symbolic models. Parallel connectionist memory and linguistic processes are hypothesized to give rise to processes that are describable at a higher level as sequential rule application. At the lower level, computation has the character of massively parallel satisfaction of soft numerical constraints; at the higher level, this can lead to competence characterizable by hard rules. Performance will typically deviate from this competence since behavior is achieved not by interpreting hard rules but by satisfying soft constraints. The result is a picture in which traditional and connectionist theoretical constructs collaborate intimately to provide an understanding of cognition. (shrink)

This paper argues for the possibility of 'artificial life' and computational evolution, first by discussing (via a highly simplified version) John von Neumann's self-reproducing automaton and then by presenting some recent work focusing on computational evolution, in which 'cellular automata', a form of parallel and decentralized computing system, are evolved via 'genetic algorithms'. It is argued that such in silico experiments can help to make sense of the question of whether we can eventually build computers that are intelligent and alive.

We examine the question of whether scientific theories can ever be complete. For two closely related reasons, we will argue that they cannot. The first reason is the inability to determine what are “valid empirical observations”, a result that is based on a self-reference Gödel/Tarski-like proof. The second reason is the existence of “meta-empirical” evidence of the inherent incompleteness of observations. These reasons, along with theoretical incompleteness, are intimately connected to the notion of belief and to theses within the philosophy (...) of science: the Quine-Duhem (and underdetermination) thesis and the observational/theoretical distinction failure. Some puzzling aspects of the philosophical theses will become clearer in light of these connections. Other results that follow are: no absolute measure of the informational content of empirical data, no absolute measure of the entropy of physical systems, and no complete computer simulation of the natural world are possible. The connections with the mathematical theorems of Gödel and Tarski reveal the existence of other connections between scientific and mathematical incompleteness: computational irreducibility, complexity, infinity, arbitrariness and self-reference. Finally, suggestions will be offered of where a more rigorous (or formal) “proof” of scientific incompleteness can be found. (shrink)

Hofstadter has introduced the notion of an explicit Henkin sentence. Roughly speaking, an explicit Henkin sentence not only asserts its own provability, as ordinary Henkin sentences do, but explicitly provides a detailed description of a proof. We provide, in this paper, a precise formalization of Hofstadter's notion and then show that true explicit Henkin sentences exist.

We are responsible for some things but not for others. In this thesis, I investigate what it takes for an entity to be responsible for something. This question has two components: agents and actions. I argue for a permissive view about agents. Entities such as groups or artificially intelligent systems may be agents in the sense required for responsibility. With respect to actions, I argue for a causal view. The relation in virtue of which agents are responsible for actions is (...) a causal one. I claim that responsibility requires causation and I develop a causal account of agency. This account is particularly apt for addressing the relationship between agency and moral responsibility and sheds light on the causal foundations of moral responsibility. (shrink)

Philosophical questions about minds and computation need to focus squarely on the mathematical theory of Turing machines (TM's). Surrogate TM's such as computers or formal systems lack abilities that make Turing machines promising candidates for possessors of minds. Computers are only universal Turing machines (UTM's)—a conspicuous but unrepresentative subclass of TM. Formal systems are only static TM's, which do not receive inputs from external sources. The theory of TM computation clearly exposes the failings of two prominent critiques, Searle's Chinese room (...) (1980) and arguments from Gödel's Incompleteness theorems (e.g., Lucas, 1961; Penrose, 1989), both of which fall short of addressing the complete TM model. Both UTM-computers and formal systems provide an unsound basis for debate. In particular, their special natures easily foster the misconception that computation entails intrinsically meaningless symbol manipulation. This common view is incorrect with respect to full-fledged TM's, which can process inputs non-formally, i.e., in a subjective and dynamically evolving fashion. To avoid a distorted understanding of the theory of computation, philosophical judgments and discussions should be grounded firmly upon the complete Turing machine model, the proper model for real computers. (shrink)

Computer software is written in languages like C, Java or Haskell. In many cases social software is expressed in natural language. The paper explores connections between the areas of natural language analysis and analysis of social protocols, and proposes an extended program for natural language semantics, where the goals of natural language communication are derived from the demands of specific social protocols.

Reading through Mechanica1 Intelligence, volume III of Alan Turing's Collected Works, one begins to appreciate just how propitious Turing's timing was. If Turing's major accomplishment in ‘On Computable Numbers’ was to expose the epistemological premises built into formalism, his main achievement in the 1940s was to recognize the extent to which this outlook both harmonized with and extended contemporary psychological thought. Turing sought to synthesize these diverse mathematical and psychological elements so as to forge a union between ‘embodied rules’ and (...) ‘learning programs’. Through their joint service in the Mechanist Thesis each would validate the other: and the frameworks from whence each derived. In this paper I will try to show how Turing's psychological thesis forces us to reassess the consequences of establishing AI on the epistemological foundation that underlies behaviourism. (shrink)