Results 1  10
of
250
Facing up to the problem of consciousness
 Journal of Consciousness Studies
, 1995
"... Consciousness poses the most baffling problems in the science of the mind. There is nothing that we know more intimately than conscious experience, but there is nothing that is harder to explain. All sorts of mental phenomena have yielded to scientific investigation in recent years, but consciousnes ..."
Abstract

Cited by 118 (2 self)
 Add to MetaCart
Consciousness poses the most baffling problems in the science of the mind. There is nothing that we know more intimately than conscious experience, but there is nothing that is harder to explain. All sorts of mental phenomena have yielded to scientific investigation in recent years, but consciousness has stubbornly resisted. Many have tried to explain it, but the
The Power of Vacillation in Language Learning
, 1992
"... Some extensions are considered of Gold's influential model of language learning by machine from positive data. Studied are criteria of successful learning featuring convergence in the limit to vacillation between several alternative correct grammars. The main theorem of this paper is that there are ..."
Abstract

Cited by 44 (11 self)
 Add to MetaCart
Some extensions are considered of Gold's influential model of language learning by machine from positive data. Studied are criteria of successful learning featuring convergence in the limit to vacillation between several alternative correct grammars. The main theorem of this paper is that there are classes of languages that can be learned if convergence in the limit to up to (n+1) exactly correct grammars is allowed but which cannot be learned if convergence in the limit is to no more than n grammars, where the no more than n grammars can each make finitely many mistakes. This contrasts sharply with results of Barzdin and Podnieks and, later, Case and Smith, for learnability from both positive and negative data. A subset principle from a 1980 paper of Angluin is extended to the vacillatory and other criteria of this paper. This principle, provides a necessary condition for circumventing overgeneralization in learning from positive data. It is applied to prove another theorem to the eff...
Learning, Action, and Consciousness: A Hybrid Approach toward Modeling Consciousness
, 1996
"... This paper is an attempt at understanding the issue of consciousness through investigating its functional role, especially in learning, and through devising hybrid neural network models that (in a qualitative manner) approximate characteristics of human consciousness. In so doing, the paper examines ..."
Abstract

Cited by 37 (19 self)
 Add to MetaCart
This paper is an attempt at understanding the issue of consciousness through investigating its functional role, especially in learning, and through devising hybrid neural network models that (in a qualitative manner) approximate characteristics of human consciousness. In so doing, the paper examines explicit and implicit learning in a variety of psychological experiments and delineates the conscious/unconscious distinction in terms of the two types of learning and their respective products. The distinctions are captured in a twolevel actionbased model Clarion. Some fundamental theoretical issues are also clarified with the help of the model. Comparisons with existing models of consciousness are made to accentuate the present approach. KEYWORDS: Neural networks, hybrid systems, consciousness, implicit learning, reinforcement learning, procedural knowledge, rule extraction, dual representation 1 INTRODUCTION 3 1 Introduction Amidst the widespread enthusiasm of recent years concerning...
QuantumInspired Computing
, 1995
"... The paper identifies and demonstrates the feasibility of a novel computational paradigm which is inspired by the principles of quantum mechanics and quantum computing. A brief history of quantum computing and basic exposition of quantum mechanics are provided, followed by a detailed description of S ..."
Abstract

Cited by 36 (5 self)
 Add to MetaCart
The paper identifies and demonstrates the feasibility of a novel computational paradigm which is inspired by the principles of quantum mechanics and quantum computing. A brief history of quantum computing and basic exposition of quantum mechanics are provided, followed by a detailed description of Shor's quantum `algorithm' for factoring very large numbers. An extension to Shor's method is described, and this leads to two further applications of `quantuminspired' methods: sorting, and the 15puzzle. In all cases, quantuminspired methods require the use of `classical' methods to determine whether the candidate answers provided by the quantuminspired methods are correct. Finally, some basic methodological principles and guidelines are provided for quantuminspired computing. The aim is not to provide a formal exposition of quantuminspired computing but to identify its novelty and potential use in tackling NPhard problems. 1 Introduction It has been estimated that every two years ...
Universal Concept of Complexity by the Dynamic Redundance Paradigm: Causal Randomness, Complete Wave Mechanics, and the Ultimate Unification of Knowledge (Naukova
, 1997
"... Abstract. This is a brief, nontechnical presentation of the main results of a book with the same title in which a new, rigorously defined concept of dynamic complexity is introduced and it is shown that it gives the complete and absolutely universal description of both representative particular cas ..."
Abstract

Cited by 26 (11 self)
 Add to MetaCart
Abstract. This is a brief, nontechnical presentation of the main results of a book with the same title in which a new, rigorously defined concept of dynamic complexity is introduced and it is shown that it gives the complete and absolutely universal description of both representative particular cases of complex dynamics and arbitrary dynamical system behaviour. This crucial extension with respect to the existing concepts is achieved due to a new, universally modified form of arbitrary dynamic equations, avoiding the usual limitations of the essentially perturbative, onedimensional approach of the canonical, linear (unitary) science (including any superficially defined, integrable 'nonlinearities'). This modified description shows that an equation describing any real behaviour with more than one effective dimension possesses many solutions, each of them being complete in the usual sense and approximately equivalent to some ordinary, 'exact ' solution of the linear science. Therefore these elementary complete solutions, called realisations, are incompatible among them and, being equivalent and thus equally probable, permanently and spontaneously replace one another. This discovery, referred to as the dynamic redundance paradigm, provides a qualitatively new understanding of the notion of existence itself and universally explains all the known patterns of dynamic behaviour within the ensuing single concept. It provides, in particular, the causal, dynamically based and consistent definition of randomness and probability (or fundamental
QuantumInspired Genetic Algorithms
 In Proceedings of the 1996 IEE InternationalConference on Evolutionary Computation(ICEC96
, 1995
"... A novel evolutionary computing method  quantum inspired genetic algorithms  is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more efficient evolutionary computing methods. The basic terminology of quantum mechanics is introduced before a comparis ..."
Abstract

Cited by 26 (2 self)
 Add to MetaCart
A novel evolutionary computing method  quantum inspired genetic algorithms  is introduced, where concepts and principles of quantum mechanics are used to inform and inspire more efficient evolutionary computing methods. The basic terminology of quantum mechanics is introduced before a comparison is made between a classical genetic algorithm and a quantum inspired method for the travelling salesperson problem. It is informally shown that the quantum inspired genetic algorithm performs better than the classical counterpart for a small domain. The paper concludes with some speculative comments concerning the relationship between quantum inspired genetic algorithms and various complexity classes. This paper will be presented at the IEEE International Conference on Evolutionary Computation (ICEC96) to be held at Nogaya, Japan, in May 1996. I. Introduction Quantuminspired computing [7] is characterised by: 1. the use of a `quantuminspired' computational method which is inspired by...
Entanglement and quantum computation
 The Geometric Universe
, 1998
"... The phenomenon of quantum entanglement is perhaps the most enigmatic feature of the formalism of quantum theory. It underlies many of the most curious and controversial aspects of the quantum mechanical description of the world. In [1] Penrose gives a delightful and accessible account of entanglemen ..."
Abstract

Cited by 26 (2 self)
 Add to MetaCart
The phenomenon of quantum entanglement is perhaps the most enigmatic feature of the formalism of quantum theory. It underlies many of the most curious and controversial aspects of the quantum mechanical description of the world. In [1] Penrose gives a delightful and accessible account of entanglement illustrated by some
Gödel machines: Fully selfreferential optimal universal selfimprovers
 Goertzel and C. Pennachin, Artificial General Intelligence
, 2006
"... Summary. We present the first class of mathematically rigorous, general, fully selfreferential, selfimproving, optimally efficient problem solvers. Inspired by Kurt Gödel’s celebrated selfreferential formulas (1931), such a problem solver rewrites any part of its own code as soon as it has found ..."
Abstract

Cited by 25 (12 self)
 Add to MetaCart
Summary. We present the first class of mathematically rigorous, general, fully selfreferential, selfimproving, optimally efficient problem solvers. Inspired by Kurt Gödel’s celebrated selfreferential formulas (1931), such a problem solver rewrites any part of its own code as soon as it has found a proof that the rewrite is useful, where the problemdependent utility function and the hardware and the entire initial code are described by axioms encoded in an initial proof searcher which is also part of the initial code. The searcher systematically and efficiently tests computable proof techniques (programs whose outputs are proofs) until it finds a provably useful, computable selfrewrite. We show that such a selfrewrite is globally optimal—no local maxima!—since the code first had to prove that it is not useful to continue the proof search for alternative selfrewrites. Unlike previous nonselfreferential methods based on hardwired proof searchers, ours not only boasts an optimal order of complexity but can optimally reduce any slowdowns hidden by the O()notation, provided the utility of such speedups is provable at all. 1
The Garden of Knowledge as a Knowledge Manifold  A Conceptual Framework for Computer Supported Subjective Education
 CID17, TRITANAD9708, DEPARTMENT OF NUMERICAL ANALYSIS AND COMPUTING SCIENCE
, 1997
"... This work presents a unied patternbased epistemological framework, called a Knowledge Manifold, for the description and extraction of knowledge from information. Within this framework it also presents the metaphor of the Garden Of Knowledge as a constructive example. Any type of KM is defined in te ..."
Abstract

Cited by 22 (14 self)
 Add to MetaCart
This work presents a unied patternbased epistemological framework, called a Knowledge Manifold, for the description and extraction of knowledge from information. Within this framework it also presents the metaphor of the Garden Of Knowledge as a constructive example. Any type of KM is defined in terms of its objective calibration protocols  procedures that are implemented on top of the participating subjective knowledgepatches. They are the procedures of agreement and obedience that characterize the coherence of any type of interaction, and which are used here in order to formalize the concept of participator consciousness in terms of the inversedirect limit duality of Category Theory.