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Improving FIFA Player Agents Decision-Making Architectures Based on Convolutional Neural Networks Through Evolutionary Techniques.

, , and . BRACIS, volume 12319 of Lecture Notes in Computer Science, page 371-386. Springer, (2020)

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Deep Active Imitation Learning in FIFA Free-Kicks Player Platforms Based on Raw Image and Object Detection State Representations., , and . ICTAI, page 1654-1658. IEEE, (2019)A multiagent player system composed by expert agents in specific game stages operating in high performance environment., , and . Appl. Intell., 48 (1): 1-22 (2018)A Deep Reinforcement Learn-Based FIFA Agent with Naive State Representations and Portable Connection Interfaces., , and . FLAIRS, page 276-281. AAAI Press, (2019)ADABA: improving the balancing between runtime and accuracy in a new distributed version of the alpha-beta algorithm., , and . Artif. Intell. Rev., 56 (5): 4255-4293 (May 2023)APHID-Draughts: Comparing the Synchronous and Asynchronous Parallelism Approaches for the Alpha-Beta Algorithm Applied to Checkers., , and . ICTAI, page 1243-1250. IEEE Computer Society, (2017)Improving FIFA Player Agents Decision-Making Architectures Based on Convolutional Neural Networks Through Evolutionary Techniques., , and . BRACIS, volume 12319 of Lecture Notes in Computer Science, page 371-386. Springer, (2020)Improving the accomplishment of a neural network based agent for draughts that operates in a distributed learning environment., , and . IRI, page 262-269. IEEE Computer Society, (2013)ADABA: An Algorithm to Improve the Parallel Search in Competitive Agents., and . ISDA (1), volume 940 of Advances in Intelligent Systems and Computing, page 475-485. Springer, (2018)Evaluating the Performance of the Deep Active Imitation Learning Algorithm in the Dynamic Environment of FIFA Player Agents., , and . ICMLA, page 228-233. IEEE, (2019)