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13

GECCO
2003
Springer

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Reinforcement Learning Estimation of Distribution Algorithm

13 years 9 months ago

Reinforcement Learning Estimation of Distribution Algorithm

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Abstract. This paper proposes an algorithm for combinatorial optimizations that uses reinforcement learning and estimation of joint probability distribution of promising solutions to generate a new population of solutions. We call it Reinforcement Learning Estimation of Distribution Algorithm (RELEDA). For the estimation of the joint probability distribution we consider each variable as univariate. Then we update the probability of each variable by applying reinforcement learning method. Though we consider variables independent of one another, the proposed method can solve problems of highly correlated variables. To compare the eﬃciency of our proposed algorithm with other Estimation of Distribution Algorithms (EDAs) we provide the experimental results of the two problems: four peaks problem and bipolar function.

Topon Kumar Paul, Hitoshi Iba

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Estimation | GECCO 2003 | Joint Probability Distribution | Reinforcement Learning |

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Added	06 Jul 2010
Updated	06 Jul 2010
Type	Conference
Year	2003
Where	GECCO
Authors	Topon Kumar Paul, Hitoshi Iba

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