inejc / mcts Goto Github PK
View Code? Open in Web Editor NEW:deciduous_tree: Domain independent implementation of Monte Carlo Tree Search methods.
License: MIT License
:deciduous_tree: Domain independent implementation of Monte Carlo Tree Search methods.
License: MIT License
In io.github.nejc92.mcts.MctsTest, after I change NUMBER_OF_ITERATIONS
from 700 to 7, there will be error:
java.lang.UnsupportedOperationException: Error: operation not supported if node not fully expanded
at io.github.nejc92.mcts.Mcts.validateBestChildComputable(Mcts.java:87)
at io.github.nejc92.mcts.Mcts.getNodesMostPromisingAction(Mcts.java:94)
at io.github.nejc92.mcts.Mcts.uctSearchWithExploration(Mcts.java:37)
at io.github.nejc92.mcts.MctsTest.playOneTicTacToeGame(MctsTest.java:31)
at io.github.nejc92.mcts.MctsTest.testUctSearch(MctsTest.java:23)
Is this a bug?
And how to tune it for chess?
I have a problem when trying to use this library for chess because getTerminalStateByPerformingSimulationFromState try to reach the end game; however, this is not feasible when it comes to chess.
Can you show me how to write the getTerminalStateByPerformingSimulationFromState for chess?
With algorithms like alpha-beta or minimax, we can specify search depth to specify strength.
How to specify strength of the mcts?
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