Monte-Carlo Tree Search (MCTS) is a heuristic to search in large trees. We employ it for concept learning in argumentation: MCTS pursues the best argumentation meant to account for a possibly inconsistent set of training examples. We provide experimental results of our approach with the search variant Upper Confidence Bounds on Tree (UCT).

Concept Learning by a Monte-Carlo Tree Search of Argumentations

CAIANIELLO, Pasquale;COSTANTINI, STEFANIA;
2014-01-01

Abstract

Monte-Carlo Tree Search (MCTS) is a heuristic to search in large trees. We employ it for concept learning in argumentation: MCTS pursues the best argumentation meant to account for a possibly inconsistent set of training examples. We provide experimental results of our approach with the search variant Upper Confidence Bounds on Tree (UCT).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11697/38060
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