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Multi-Agent Reinforcement Learning in Games: Research and Applications. [PDF]
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Performance evaluation and multi-objective optimization of protective slurry seal asphalt mixtures incorporating foundry waste filler and silver nanoparticles. [PDF]
Sci RepMofrad VB +4 more
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Revisiting evolutionary programming
SPIE Proceedings, 1998Evolutionary programming is a method for simulating evolution that has been investigated for almost 40 years. When originally introduced, the available computing equipment was quite slow and difficult to use as measured by current standards. This paper provides a series of experiments that follow the framework of the original approach from the early ...
David B. Fogel, Kumar Chellapilla
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Parallel evolutionary programming
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753), 2005This work presents a study of parallel evolutionary programming (EP). The paper is divided into two parts. The first part proposes a concept of parallel EP. Four numerical functions are used to compare the performance between the serial algorithm and the parallel algorithm.
null Shisanu Tongchim, null Xin Yao
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[1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers, 2002
A brief review of efforts is simulated evolution is given. Evolutionary programming is a stochastic optimization technique that is useful for discovering the extrema of a nonlinear function. To implement such a search, several high-level parameters must be chosen, such as the amount of mutational noise, the severity of the mutation noise, and so forth.
D.B. Fogel, L.J. Fogel, J.W. Atmar
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A brief review of efforts is simulated evolution is given. Evolutionary programming is a stochastic optimization technique that is useful for discovering the extrema of a nonlinear function. To implement such a search, several high-level parameters must be chosen, such as the amount of mutational noise, the severity of the mutation noise, and so forth.
D.B. Fogel, L.J. Fogel, J.W. Atmar
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Directed Evolutionary Programming: Towards an Improved Performance of Evolutionary Programming
2006 IEEE International Conference on Evolutionary Computation, 2006Evolutionary programming (EP) is one of the main classes of evolutionary algorithms (EAs). Improving existing EAs is necessary in order to achieve better results and overcome their costly computational complexity. In this paper, we present a new version of EP called Directed Evolutionary Programming (DEP) in which more directing strategies with learned
A.-R. Hedar, M. Fukushima
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Evolutionary Program Sketching
2017Program synthesis can be posed as a satisfiability problem and approached with generic SAT solvers. Only short programs can be however synthesized in this way. Program sketching by Solar-Lezama assumes that a human provides a partial program (sketch), and that synthesis takes place only within the uncompleted parts of that program.
Iwo Błądek, Krzysztof Krawiec
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Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation, 2009
The Evolutionary Meta Programming (EMP) approach towards the evolution of computer programs is presented. An EMP system is divided into two interacting parts: The Host Environment, and the Target Environment. Programs are evolved in an arbitrary target language by the Host Environment and are injected into the Target Environment, where they are ...
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The Evolutionary Meta Programming (EMP) approach towards the evolution of computer programs is presented. An EMP system is divided into two interacting parts: The Host Environment, and the Target Environment. Programs are evolved in an arbitrary target language by the Host Environment and are injected into the Target Environment, where they are ...
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