This cutting edge volume provides an overview of the dynamic new field of cyberphilosophy – the intersection of philosophy and computing.

Computation and philosophy intersect three times in this essay. Computation is considered as an object, as a method, and as a model used in a certain line of philosophical inquiry concerning the relation of mind to matter. As object, the question considered is whether computation and related notions of mental representation constitute the best ways to conceive of how physical systems give rise to mental properties. As method and model, the computational techniques of artificial life and embodied evolutionary connectionism are (...) used to conduct prosthetically enhanced thought experiments concerning the evolvability of mental representations. Central to this essay is a discussion of the computer simulation and evolution of three-dimensional synthetic animals with neural network controllers. The minimally cognitive behavior of finding food by exhibit- ing positive chemotaxis is simulated with swimming and walking creatures. These simulations form the basis of a discussion of the evolutionary and neurocomputa- tional bases of the incremental emergence of more complex forms of cognition. Other related work has been used to attack computational and representational theories of cognition. In contrast, I argue that the proper understanding of the evolutionary emergence of minimally cognitive behaviors is computational and representational through and through. (shrink)

Hilary Putnam has argued that computational functionalism cannot serve as a foundation for the study of the mind, as every ordinary open physical system implements every finite-state automaton. I argue that Putnam's argument fails, but that it points out the need for a better understanding of the bridge between the theory of computation and the theory of physical systems: the relation of implementation. It also raises questions about the class of automata that can serve as a basis for understanding the (...) mind. I develop an account of implementation, linked to an appropriate class of automata, such that the requirement that a system implement a given automaton places a very strong constraint on the system. This clears the way for computation to play a central role in the analysis of mind. (shrink)

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on representation disappears. In this paper we outline our approach to incrementally building complete intelligent Creatures. The fundamental decomposition of the intelligent system is not into independent information processing units which must interface with each other via representations. Instead, the intelligent system is decomposed into independent and parallel activity (...) producers which all interface directly to the world through perception and action, rather than interface to each other particularly much. The notions of central and peripheral systems evaporateeverything is both central and peripheral. Based on these principles we have built a very successful series of mobile robots which operate without supervision as Creatures in standard office environments. (shrink)

Artificial life (also known as “ALife”) is a broad, interdisciplinary endeavor that studies life and life-like processes through simulation and synthesis. The goals of this activity include modelling and even creating life and life-like systems, as well as developing practical applications using intuitions and methods taken from living systems. Artificial life both illuminates traditional philosophical questions and raises new philosophical questions. Since both artificial life and philosophy investigate the essential nature of certain fundamental aspects of reality like life and adaptation, (...) artificial life offers philosophy a new perspective on these phenomena. This chapter provides an introduction to current research in artificial life and explains its philosophical implications. (shrink)

This volume tackles the slippery subject of 'meaning'.

Presents a mathematically rigorous, philosophically sound foundation for a science of information.

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)

Much as we would like to conceive empirical thought as rationally grounded in experience, pitfalls await anyone who tries to articulate this position, and ...

The mathematical theory of communication.

INTRODUCTION: TWO KINDS OF RLDUCTIONISM The man who laughs is the one who has not yet heard the terrible news. BERTHOLD BRECHT I propose, in this book, ...

Semantic Engines: An Introduction to Mind Design, John C. Haugeland; Computer Science as Empirical Inquiry: Symbols and Search, Alan Newell and Herbert A. Simon; Complexity and the Study of Artificial and Human Intelligence, Zenon Pylyshyn; A Framework for Representing Knowledge, Marvin Minsky; Artificial Intelligence---A Personal View, David Marr; Artificial Intelligence Meets Natural Stupidity, Drew McDermott; From Micro-Worlds to Knowledge Representation: AI at an Impasse, Hubert L. Dreyfus; Reductionism and the Nature of Psychology, Hilary Putnam; Intentional Systems, Daniel C. Dennett; The (...) Nature and Plausibility of Cognitivism, John C. Haugeland; Minds, Brains, and Programs, John R. Searle; MethodologicalSolipsism Considered as a Research Strategy in Cognitive Psychology, Jerry A. Fodor; The Material Mind, Donald Davidson. (shrink)

In this book van Fraassen develops an alternative to scientific realism by constructing and evaluating three mutually reinforcing theories.

The purpose of this essay is to determinewhat exactly is meant by the claimcomputer ethics is unique, a position thatwill henceforth be referred to as the CEIUthesis. A brief sketch of the CEIU debate is provided,and an empirical case involving a recentincident of cyberstalking is briefly consideredin order to illustrate some controversialpoints of contention in that debate. To gain aclearer understanding of what exactly isasserted in the various claims about theuniqueness of computer ethics, and to avoidmany of the confusions currently (...) associatedwith the term ``unique'', a precise definition ofthat term is proposed. We then differentiatetwo distinct and radically differentinterpretations of the CEIU thesis, based onarguments that can be found in the relevantcomputer ethics literature. The twointerpretations are critically analyzed andboth are shown to be inadequate in establishingthe CEIU thesis. We then examine and reject twoassumptions implicit in arguments advanced bothby CEIU advocates and their opponents. Inexposing and rejecting these assumptions, wesee why it is not necessary to accept theconclusions reached by either side in thisdebate. Finally, we defend the view thatcomputer ethics issues are both philosophicallyinteresting and deserving of our attention,regardless of whether those issues might alsohappen to be unique ethical issues. (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)

There are different ways to present a Presidential Address to the APA; the one I have chosen is simply to report on work that I am doing right now, on work in progress. I am going to present some of my further explorations into the computational model of the mind.\**.

This book expounds a system of ideas about the nature of mathematics which Michael Resnik has been elaborating for a number of years. In calling mathematics a science he implies that it has a factual subject-matter and that mathematical knowledge is on a par with other scientific knowledge; in calling it a science of patterns he expresses his commitment to a structuralist philosophy of mathematics. He links this to a defense of realism about the metaphysics of mathematics--the view that mathematics (...) is about things that really exist. (shrink)

In this fascinating autobiography from the foremost genius of twentieth-century physics, Max Planck tells the story of his life, his aims, and his thinking. Published posthumously, the papers in this volume were written for the general reader and make accessible his scientific theories as well as his philosophical ideals, including his thoughts on ethics and morals. Max (Karl Ernst Ludwig) Planck was a German physicist and philosopher known for his quantum theory, for which he won the Nobel Prize in Physics (...) in 1918. Planck was born in Kiel, Germany, in 1858 to an academic family, and he valued education from a young age. He attended the Universities of Munich and Berlin to study physics under the great scientific leaders Kirchhoff and Helmholtz. His early work mainly focused on the study of thermodynamics, and in 1900 he published a paper on his quantum theory that would change the face of modern physics. Planck worked as a professor at Berlin University his entire life, and he also served as the president of the Kaiser Wilhelm Society for the Promotion of Science. During World War II, Planck experienced great hardships while he remained in Germany but openly opposed the Nazi regime. One of his two sons was executed during this time for an unsuccessful attempt on Hitler's life, and Planck's home in Berlin was eventually bombed. He continued to write on physics and philosophy until his death in 1947. (shrink)

The emperor's new mind (hereafter Emperor) is an attempt to put forward a scientific alternative to the viewpoint of according to which mental activity is merely the acting out of some algorithmic procedure. John Searle and other thinkers have likewise argued that mere calculation does not, of itself, evoke conscious mental attributes, such as understanding or intentionality, but they are still prepared to accept the action the brain, like that of any other physical object, could in principle be simulated by (...) a computer. In Emperor I go further than this and suggest that the outward manifestations ofconscious mental activity cannot even be properly simulated by calculation. To support this view, I use various arguments to show that the results of mathematical insight, in particular, do not seem to be obtained algorithmically. The main thrust ofthis work, however, is to present an overview ofthe present state of physical understanding and to show that an important gap exists at the point where, quantum and classical physics meet, as well as to speculate on how the conscious brain might be taking advantage ofwhatever new physics is needed to fill this gap to achieve its nonalgorithmic effects. (shrink)

On the occasion of a first conference on Cognitive Science, it seems appropriate to review the basis of common understanding between the various disciplines. In my estimate, the most fundamental contribution so far of artificial intelligence and computer science to the joint enterprise of cognitive science has been the notion of a physical symbol system, i.e., the concept of a broad class of systems capable of having and manipulating symbols, yet realizable in the physical universe. The notion of symbol so (...) defined is internal to this concept, so it becomes a hypothesis that this notion of symbols includes the symbols that we humans use every day of our lives. In this paper we attempt systematically, but plainly, to lay out the nature of physical symbol systems. Such a review is in ways familiar, but not thereby useless. Restatement of fundamentals is an important exercise. (shrink)

the _algorithmic_, and the _implementational_; Zenon Pylyshyn (1984) calls them the _semantic_, the _syntactic_, and the _physical_; and textbooks in cognitive psychology sometimes call them the levels of _content_, _form_, and _medium_ (e.g. Glass, Holyoak, and Santa 1979).

Computation and philosophy intersect three times in this essay. Computation is considered as an object, as a method, and as a model used in a certain line of philosophical inquiry concerning the relation of mind to matter. As object, the question considered is whether computation and related notions of mental representation constitute the best ways to conceive of how physical systems give rise to mental properties. As method and model, the computational techniques of artificial life and embodied evolutionary connectionism are (...) used to conduct prosthetically enhanced thought experiments concerning the evolvability of mental representations. Central to this essay is a discussion of the computer simulation and evolution of three‐dimensional synthetic animals with neural network controllers. The minimally cognitive behavior of finding food by exhibiting positive chemotaxis is simulated with swimming and walking creatures. These simulations form the basis of a discussion of the evolutionary and neurocomputational bases of the incremental emergence of more complex forms of cognition. Other related work has been used to attack computational and representational theories of cognition. In contrast, I argue that the proper understanding of the evolutionary emergence of minimally cognitive behaviors is computational and representational through and through. (shrink)

In this article, Lucas maintains the falseness of Mechanism - the attempt to explain minds as machines - by means of Incompleteness Theorem of Gödel. Gödel’s theorem shows that in any system consistent and adequate for simple arithmetic there are formulae which cannot be proved in the system but that human minds can recognize as true; Lucas points out in his turn that Gödel’s theorem applies to machines because a machine is the concrete instantiation of a formal system: therefore, for (...) every machine consistent and able of doing simple arithmetic, there is a formula that it can’t produce as true but that we can see to be true, and so human minds and machines have to be different. Lucas considers as well in this article some possible objections to his argument: for any Gödelian formula we could, for instance, construct a machine able to produce it or we could put the Gödelian formulae that we had proved as axioms of a further machine. However - as Lucas underlines - for every of such machines we could again formulate another Gödelian formula, the Gödelian formula of these machines, that they are not able to proof but that we can recognize as true. More general arguments, such as the possibility to escape Gödelian argument by suggesting that Gödel’s theorem applies to consistent systems while we could be inconsistent ones, are moreover refuted by Lucas by maintaining that our inconsistency corresponds to occasional malfunctioning of a machine and not to his normal inconsistency; indeed, a inconsistent machine is characterized by producing any statement, on the contrary human being are selective and not disposed to assert anything. (shrink)

Gödei's Theorem seems to me to prove that Mechanism is false, that is, that minds cannot be explained as machines. So also has it seemed to many other people: almost every mathematical logician I have put the matter to has confessed to similar thoughts, but has felt reluctant to commit himself definitely until he could see the whole argument set out, with all objections fully stated and properly met. This I attempt to do.

How do rational minds make contact with the world? The empiricist tradition sees a gap between mind and world, and takes sensory experience, fallible as it is, to provide our only bridge across that gap. In its crudest form, for example, the traditional idea is that our minds consult an inner realm of sensory experience, which provides us with evidence about the nature of external reality. Notoriously, however, it turns out to be far from clear that there is any viable (...) conception of experience which allows it to do the job. The original problem is to show that thought is rationally constrained by external reality. If sensory experience is to provide the solution--in particular, if it is to provide the answer to sceptical challenges--it must therefore meet two criteria. First, it must itself be `receptive'--i.e., appropriately constrained by external reality. Second, it must be the kind of thing that can enter into a logical or rational relationship with belief--it must already be `conceptual,' in other words. In arguing against the idea that anything could serve both roles, Wilfred Sellars termed this conception of experience "the Myth of the Given.". (shrink)

Turing's celebrated 1950 paper proposes a very general methodological criterion for modelling mental function: total functional equivalence and indistinguishability. His criterion gives rise to a hierarchy of Turing Tests, from subtotal ("toy") fragments of our functions (t1), to total symbolic (pen-pal) function (T2 -- the standard Turing Test), to total external sensorimotor (robotic) function (T3), to total internal microfunction (T4), to total indistinguishability in every empirically discernible respect (T5). This is a "reverse-engineering" hierarchy of (decreasing) empirical underdetermination of the theory (...) by the data. Level t1 is clearly too underdetermined, T2 is vulnerable to a counterexample (Searle's Chinese Room Argument), and T4 and T5 are arbitrarily overdetermined. Hence T3 is the appropriate target level for cognitive science. When it is reached, however, there will still remain more unanswerable questions than when Physics reaches its Grand Unified Theory of Everything (GUTE), because of the mind/body problem and the other-minds problem, both of which are inherent in this empirical domain, even though Turing hardly mentions them. (shrink)