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Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2011
Genetic programming emerged in the early 1990's as one of the most exciting new evolutionary algorithm paradigms. It has rapidly grown into a thriving area of research and application. While sharing the evolutionary inspired algorithm principles of a genetic algorithm, it differs by exploiting an executable genome.
Silva S. +4 more
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Genetic programming emerged in the early 1990's as one of the most exciting new evolutionary algorithm paradigms. It has rapidly grown into a thriving area of research and application. While sharing the evolutionary inspired algorithm principles of a genetic algorithm, it differs by exploiting an executable genome.
Silva S. +4 more
+6 more sources
Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546), 2002
Programming is a process of optimization; taking a specification, which tells us what we want, and transforming it into an implementation, a program, which causes the target system to do exactly what we want. Conventionally, this optimization is achieved through manual design.
Michael A. Lones, Andy M. Tyrrell
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Programming is a process of optimization; taking a specification, which tells us what we want, and transforming it into an implementation, a program, which causes the target system to do exactly what we want. Conventionally, this optimization is achieved through manual design.
Michael A. Lones, Andy M. Tyrrell
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2006
The goal of getting computers to automatically solve problems is central to artificial intelligence, machine learning, and the broad area encompassed by what Turing called machine intelligence (Turing 1948, 1950).
Poli, Riccardo, Koza, John
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The goal of getting computers to automatically solve problems is central to artificial intelligence, machine learning, and the broad area encompassed by what Turing called machine intelligence (Turing 1948, 1950).
Poli, Riccardo, Koza, John
+5 more sources
Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, 2015
Semantic genetic programming is a recent, rapidly growing trend in Genetic Programming (GP) that aims at opening the 'black box' of the evaluation function and make explicit use of more information on program behavior in the search. In the most common scenario of evaluating a GP program on a set of input-output examples (fitness cases), the semantic ...
Alberto Moraglio, Krzysztof Krawiec
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Semantic genetic programming is a recent, rapidly growing trend in Genetic Programming (GP) that aims at opening the 'black box' of the evaluation function and make explicit use of more information on program behavior in the search. In the most common scenario of evaluating a GP program on a set of input-output examples (fitness cases), the semantic ...
Alberto Moraglio, Krzysztof Krawiec
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Reinforced Genetic Programming
Genetic Programming and Evolvable Machines, 2001Summary: This paper introduces the Reinforced Genetic Programming (RGP) system, which enhances standard tree-based genetic programming (GP) with reinforcement learning (RL). RGP adds a new element to the GP function set: monitored action-selection points that provide hooks to a reinforcement-learning system.
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Expressive Genetic Programming
Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2013The language in which evolving programs are expressed can have significant impacts on the problem-solving capabilities of a genetic programming system. These impacts stem both from the absolute computational power of the languages that are used, as elucidated by formal language theory, and from the ease with which various computational structures can ...
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