A vast amount of work has been done in recent years on the design, analysis, implementation and verification of special purpose parallel computing systems. This paper presents a survey of various aspects of this work. A long, but by no means complete, bibliography is given. 1. Introduction Turing [365] demonstrated that, in principle, a single general purpose sequential machine could be designed which would be capable of efficiently performing any computation which could be performed by a special purpose sequential machine. The importance of this universality result for subsequent practical developments in computing cannot be overstated. It showed that, for a given computational problem, the additional efficiency advantages which could be gained by designing a special purpose sequential machine for that problem would not be great. Around 1944, von Neumann produced a proposal [66, 389] for a general purpose storedprogram sequential computer which captured the fundamental principles of...

Abstract — In this paper, we move toward offering psychological benchmarks by which to measure success in building increasingly human-like robots. By psychological benchmarks we mean categories of interaction that capture conceptually fundamental aspects of human life, specified abstractly enough so as to resist their identity as a mere psychological instrument, but capable of being translated into testable empirical propositions. Six possible benchmarks are considered: autonomy, imitation, intrinsic moral value, moral accountability, privacy, and reciprocity. Finally, we discuss how getting the right group of benchmarks in human-robot interaction will, in future years, help inform on the foundational question of what constitutes essential features of being human.

Abstract. The Turing Test is one of the most disputed topics in arti cial intelligence, philosophy of mind, and cognitive science. This paper is a review of the past 50 years of the Turing Test. Philosophical debates, practical developments and repercussions in related disciplines are all covered. We discuss Turing's ideas in detail and present the important comments that have been made on them. Within this context, behaviorism, consciousness, the `other minds ' problem, and similar topics in the philosophy of mind are discussed. We also cover the sociological and psychological aspects of the Turing Test. Finally, welook at the current situation and analyze the programs that have been developed with the aim of passing the Turing Test. We conclude that the Turing Test has been, and will continue to be, an in uential and controversial topic.

A myth has arisen concerning Turing's paper of 1936, namely that Turing set forth a fundamental principle concerning the limits of what can be computed by machine - a myth that has passed into cognitive science and the philosophy of mind, to wide and pernicious effect. This supposed principle, sometimes incorrectly termed the 'Church-Turing thesis', is the claim that the class of functions that can be computed by machines is identical to the class of functions that can be computed by Turing machines. In point of fact Turing himself nowhere endorses, nor even states, this claim (nor does Church). I describe a number of notional machines, both analogue and digital, that can compute more than a universal Turing machine. These machines are exemplars of the class of nonclassical computing machines. Nothing known at present rules out the possibility that machines in this class will one day be built, nor that the brain itself is such a machine. These theoretical considerations undercut a numb...

. A rule-based expert system is demonstrated to have both a symbolic computational network representation and a sub-symbolic connectionist representation. These alternate views enhance the usefulness of the original system by facilitating introduction of connectionist learning methods into the symbolic domain. The connectionist representation learns and stores metaknowledge in highly connected subnetworks and domain knowledge in a sparsely connected expert network superstructure. The total connectivity of the neural network representation approximates that of real neural systems and hence avoids scaling and memory stability problems associated with other connectionist models. Keywords. symbolic AI, connectionist AI, connectionism, neural networks, learning, reasoning, expert networks, expert systems, symbolic models, sub-symbolic models. y Paper given to the symposium Approaches to Cognition, the fifteenth annual Symposium in Philosophy held at the University of North Carolina, Gree...

Alan Turing proposed an interactive test to replace the question "Can machines think?" This test has become known as the Turing Test and its validity for determining intelligence or thinking is still in question. Struggling with the validity of long proofs, program correctness, computational complexity and cryptography, theoreticians developed interactive proof systems. By formalizing the Turing Test as an interactive proof system and by employing results from complexity theory, this paper investigates the power and limitations of the Turing Test. In particular, if human intelligence subsumes machine intelligence, and human intelligence is not simulatable by any bounded machine, then the Turing Test can distinguish humans and machines to within arbitrarily high probability. This paper makes no claim about the Turing Test's sufficiency to distinguish humans and machines. Rather, through its formalization this paper gives several ramifications involving the acceptance or rejection of the...

Searle has recently used two adaptations of his Chinese room argument in an attack on connectionism. I show that these new forms of the argument are fallacious. First I give an exposition and rebuttal of the original Chinese room argument, and a brief introduction to the essentials of connectionism. 2 Searle launched his now famous Chinese room argument in 1980. 1 His target was traditional program-writing, symbol-crunching AI. Since that time the connectionist revolution has taken place, leaving AI and cognitive science considerably altered. Searle has recently used two adaptations of the Chinese room argument in an attack on connectionism. 2 I shall show that these new forms of the argument are fallacious. First, I will give an exposition and rebuttal of the original Chinese room argument, and a brief introduction to the essentials of connectionism. The Chinese Room Argument Consider a hypothetical AI program that responds intelligently, in written Chinese, to an input of Chine...

Searle’s arguments that intelligence cannot arise from formal programs are refuted by arguing that his analogies and thought-experiments are fundamentally flawed: he imagines a world in which computation is free. It is argued instead that although cognition may in principle be realized by symbol processing machines, such a computation is likely to have resource requirements that would prevent a symbol processing program for cognition from being designed, implemented, or executed. In the course of the argument the following observations are made: (1) A system can have knowledge, but no understanding. (2) Understanding is a method by which cognitive computations are carried out with limited resources. (3) Introspection is inadequate for analyzing the mind. (4) Simulation of the brain by a computer is unlikely not because of the massive computational power of the brain, but because of the overhead required when one model of computation is simulated by another. (5) Intentionality is a property that arises from systems of sufficient computational power that have the appropriate design. (6) Models of cognition can be developed in direct analogy with technical results from the field of computational complexity theory. Penrose [30] has stated...I am inclined to think (though, no doubt, on quite inadequate grounds) that unlike the basic question of computability itself, the issues of complexity theory are not quite the central ones in relation to mental phenomena. On the contrary, I intend to demonstrate that the principles of computational complexity theory can give insights into cognition. In 1980, Searle [36] published a critique of Artificial Intelligence that almost immediately caused a flurry of debate and commentary in academic circles. The paper distinguishes

Abstract: Consciousness is only marginally relevant to artificial intelligence (AI), because to most researchers in the field other problems seem more pressing. However, there have been proposals for how consciousness would be accounted for in a complete computational theory of the mind, from theorists such as Dennett, Hofstadter, McCarthy, McDermott, Minsky, Perlis, Sloman, and Smith. One can extract from these speculations a sketch of a theoretical synthesis, according to which consciousness is the property a system has by virtue of modeling itself as having sensations and making free decisions. Critics such as Harnad and Searle have not succeeded in demolishing a priori this or any other computational theory, but no such theory can be verified or refuted until and unless AI is successful in finding computational solutions of difficult problems such as vision, language, and locomotion. 1

Abstract. The second part of this survey examines biocomputing in intact multicellular organisms. The parallelism between creative problem solving and evolution is emphasized: both processes invoke heuristic searching and feature modularity prominently. Simonton’s chance-configuration theory of creative problem solving is recast in terms of pattern recognition and analyzed in terms of parallel and sequential processing. An attempt is made to demystify the creative process that is commonly thought to be the monopoly of geniuses. It is shown that the procedures utilized in high creativity and in everyday ingenuity are fundamentally the same, but geniuses push the creative process to the extreme. A re-interpretation of Freud’s concept of the unconscious in terms of selective attention is invoked to dispel the mystery surrounding the introspective account of Henri Poincaré on mathematical creation. Among the many attributes of consciousness, the elusive free will problem is singled out for analysis in terms of biological control laws. While free will is a philosophical problem, the conflict of free will and determinism can be treated as