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Beyond Turing Machines
"... In this paper we describe and analyze models of problem solving and computation going beyond Turing Machines. Three principles of extending the Turing Machine's expressiveness are identified, namely, by interaction, evolution and infinity. Several models utilizing the above principles are present ..."
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Cited by 32 (4 self)
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In this paper we describe and analyze models of problem solving and computation going beyond Turing Machines. Three principles of extending the Turing Machine's expressiveness are identified, namely, by interaction, evolution and infinity. Several models utilizing the above principles are presented. Other
$Calculus of Bounded Rational Agents: Flexible Optimization as Search under Bounded Resources in Interactive Systems
 FUNDAMENTA INFORMATICAE
, 2005
"... This paper presents a novel model for resource bounded computation based on process algebras. ..."
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Cited by 6 (4 self)
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This paper presents a novel model for resource bounded computation based on process algebras.
Toward a theory of evolutionary computation
 BIOSYSTEMS
, 2005
"... We outline a theory of evolutionary computation using a formal model of evolutionary computation  the Evolutionary Turing Machine  which is introduced as the extension of the Turing Machine model. Evolutionary Turing Machines provide a better and a more complete model for evolutionary computing ..."
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Cited by 2 (1 self)
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We outline a theory of evolutionary computation using a formal model of evolutionary computation  the Evolutionary Turing Machine  which is introduced as the extension of the Turing Machine model. Evolutionary Turing Machines provide a better and a more complete model for evolutionary computing than conventional Turing Machines, algorithms, and Markov chains. The convergence and convergence rate are defined and investigated in terms of this new model. The sufficient conditions needed for the completeness and optimality of evolutionary search are investigated. In particular, the notion of the total optimality as an instance of the multiobjective optimization of the Universal Evolutionary Turing Machine is introduced. This provides an automatic way to deal with the intractability of evolutionary search by optimizing the quality of solutions and search costs simultaneously. Based on a new model a very flexible classification of optimization problem hardness for the evolutionary techniques is proposed.