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Improving Reinforcement Learning Results with Qualitative Spatial Representation.

, , , , and . BRACIS, page 151-156. IEEE Computer Society, (2017)

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Intelligent trading systems: a sentiment-aware reinforcement learning approach., , , and . ICAIF, page 40:1-40:9. ACM, (2021)Controlling Gene Regulatory Networks with FQI-SARSA., , and . BRACIS, page 216-221. IEEE Computer Society, (2017)Control of Gene Regulatory Networks Basin of Attractions with Batch Reinforcement Learning., , and . BRACIS, page 127-132. IEEE Computer Society, (2018)A Visual Memory System for Humanoid Robots., , , and . LARS/SBR/WRE, page 426-431. IEEE, (2018)Specializing Inter-Agent Communication in Heterogeneous Multi-Agent Reinforcement Learning using Agent Class Information., and . CoRR, (2020)Uso de heurísticas para a aceleração do aprendizado por reforço.. University of São Paulo, Brazil, (2004)ndltd.org (oai:teses.usp.br:tde-28062005-191041).Improving Reinforcement Learning Results with Qualitative Spatial Representation., , , , and . BRACIS, page 151-156. IEEE Computer Society, (2017)MASDES-DWMV: Model for Dynamic Ensemble Selection Based on Multiagent System and Dynamic Weighted Majority Voting., , , , and . MICAI (2), volume 12469 of Lecture Notes in Computer Science, page 419-434. Springer, (2020)Object Detection under Constrained Hardware Scenarios: A Comparative Study of Reduced Convolutional Network Architectures., , , , , and . LARS/SBR/WRE, page 25-30. IEEE, (2019)Comparing Vision-Based Monte-Carlo Localization Methods., , and . LARS/SBR/WRE, page 437-442. IEEE, (2018)