Evolutionary Algorithms for Reinforcement Learning
نویسندگان
چکیده
منابع مشابه
Evolutionary Algorithms for Reinforcement Learning
There are two distinct approaches to solving reinforcement learning problems, namely, searching in value function space and searching in policy space. Temporal di erence methods and evolutionary algorithms are well-known examples of these approaches. Kaelbling, Littman and Moore recently provided an informative survey of temporal di erence methods. This article focuses on the application of evo...
متن کاملEvolutionary Algorithms for Reinforcement
There are two distinct approaches to solving reinforcement learning problems, namely, searching in value function space and searching in policy space. Temporal diierence methods and evolutionary algorithms are well-known examples of these approaches. Kaelbling, Littman and Moore recently provided an informative survey of temporal diierence methods. This article focuses on the application of evo...
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The research reported in this paper is concerned with assessing the usefulness of reinforcment learning (RL) for on-line calibration of parameters in evolutionary algorithms (EA). We are running an RL procedure and the EA simultaneously and the RL is changing the EA parameters on-the-fly. We evaluate this approach experimentally on a range of fitness landscapes with varying degrees of ruggednes...
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In this paper we study the combination of two powerful approaches, evolutionary topology optimization (ENZO) and Tempoal Diierence Learning (TD()) which is up to our knowledge the rst time. Temporal Diierence Learning was proven to be a well suited technique for learning strategies for solving reinforcement problems based on neural network models , whereas evolutionary topology optimization is ...
متن کاملAlgorithms for Reinforcement Learning
Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner’s predictions. Further, the predictions may have long term effects through influ...
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ژورنال
عنوان ژورنال: Journal of Artificial Intelligence Research
سال: 1999
ISSN: 1076-9757
DOI: 10.1613/jair.613