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Learning to Evaluate Chess Positions with Deep Neural Networks and Limited Lookahead., , , and . ICPRAM, page 276-283. SciTePress, (2018)Approximating two value functions instead of one: towards characterizing a new family of Deep Reinforcement Learning algorithms, , , and . (2019)cite arxiv:1909.01779.Safe and Psychologically Pleasant Traffic Signal Control with Reinforcement Learning using Action Masking., and . ITSC, page 951-958. IEEE, (2022)VDSC: Enhancing Exploration Timing with Value Discrepancy and State Counts., , and . CoRR, (2024)Deep Quality-Value (DQV) Learning., , , and . BNAIC/BENELEARN, volume 2491 of CEUR Workshop Proceedings, CEUR-WS.org, (2019)QVMix and QVMix-Max: Extending the Deep Quality-Value Family of Algorithms to Cooperative Multi-Agent Reinforcement Learning., , , , , and . CoRR, (2020)Forest Fire Control with Learning from Demonstration and Reinforcement Learning., , , and . IJCNN, page 1-8. IEEE, (2020)A Deep Convolutional Neural Network for Location Recognition and Geometry based Information., , , , and . ICPRAM, page 27-36. SciTePress, (2018)Advances in Digital Music Iconography: Benchmarking the detection of musical instruments in unrestricted, non-photorealistic images from the artistic domain., , , , , , , and . Digit. Humanit. Q., (2021)On the Transferability of Winning Tickets in Non-natural Image Datasets., , and . VISIGRAPP (5: VISAPP), page 59-69. SCITEPRESS, (2021)