Titlebook: Computer Games; 7th Workshop, CGW 20 Tristan Cazenave,Abdallah Saffidine,Nathan Sturtev Conference proceedings 2019 Springer Nature Switzer

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Communications in Computer and Information Sciencehttp://image.papertrans.cn/c/image/233548.jpg

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Spatial Average Pooling for Computer Gouse reinforcement learning to train a policy and a value network. These networks are used in a MCTS algorithm to provide strong computer Go players. In this paper we propose to improve the architecture of a value network using Spatial Average Pooling.

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Conference proceedings 2019rence on Artificial Intelligence, IJCAI 2018 in Stockholm, Sweden, in July 2018..The 8 full papers presented in this volume were carefully reviewed and selected from 15 submissions. They cover a wide range of topics related to video games; general game playing.- machine learning and Monte Carlo tree search..

烦忧

A Bibliography of CALL: Teachersomplex games is still not possible. However, the abundance of existing game data makes StarCraft II an ideal testbed for machine learning. We attempt to use this for establishing winner predictors that in strong contrast to existing methods rely on partial information available to one player only. S

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endoscopy

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Aerate

Evaluation in Education and Human Services human intervention. The standard game representation language GDL has recently been extended so as to include games with incomplete information. The so-called Lifted HyperPlay technique, which is based on model sampling, provides a state-of-the-art solution to general game playing with incomplete i

Optometrist

https://doi.org/10.1007/978-981-10-8648-9use reinforcement learning to train a policy and a value network. These networks are used in a MCTS algorithm to provide strong computer Go players. In this paper we propose to improve the architecture of a value network using Spatial Average Pooling.

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