Lucas, Simon M and Samothrakis, Spyridon and Pérez, Diego (2014) Fast Evolutionary Adaptation for Monte Carlo Tree Search. In: UNSPECIFIED, ? - ?.
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Official URL: https://doi.org/10.1007/978-3-662-45523-4
Abstract
This paper describes a new adaptive Monte Carlo Tree Search (MCTS) algorithm that uses evolution to rapidly optimise its performance. An evolutionary algorithm is used as a source of control parameters to modify the behaviour of each iteration (i.e. each simulation or roll-out) of the MCTS algorithm; in this paper we largely restrict this to modifying the behaviour of the random default policy, though it can also be applied to modify the tree policy.
Item Type: | Conference or Workshop Item (Paper) |
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Additional Information: | Published proceedings: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Elements |
Depositing User: | Elements |
Date Deposited: | 04 Dec 2014 13:31 |
Last Modified: | 15 Jan 2022 00:31 |
URI: | http://repository.essex.ac.uk/id/eprint/11981 |
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