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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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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)A Deep Reinforcement Learn-Based FIFA Agent with Naive State Representations and Portable Connection Interfaces., , and . FLAIRS, page 276-281. AAAI Press, (2019)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)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)Investigating the Performance of Optimization Techniques on Deep Learning Models to Identify Dota2 Game Events., , , , and . VISIGRAPP (4: VISAPP), page 881-888. SCITEPRESS, (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)Deep Learning-Based Models for Performing Multi-Instance Multi-Label Event Classification in Gameplay Footage., , , and . VISIGRAPP (3): VISAPP, page 110-121. SCITEPRESS, (2024)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)Investigating the Performance of Various Deep Neural Networks-based Approaches Designed to Identify Game Events in Gameplay Footage., , , and . Proc. ACM Comput. Graph. Interact. Tech., 5 (1): 8:1-8:17 (2022)