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Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets
Robust Risk-Sensitive Reinforcement Learning Agents for Trading Markets
*Y. Gao, K. Y. C. Lui, and P. Hernandez-Leal. International Conference on Machine Learning Workshop (ICML), 2021
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Temporally Extended Auxiliary Tasks
Temporally Extended Auxiliary Tasks
C. Sherstan, B. Kartal, P. Hernandez-Leal, and M. E. Taylor. International Conference on Autonomous Agents and Multiagent Systems Workshop on Adaptive and Learning Agents (AAMAS), 2020
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Multi Type Mean Field Reinforcement Learning
Multi Type Mean Field Reinforcement Learning
S. Subramanian, P. Poupart, M. E. Taylor, and N. Hegde. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2020
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Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents
Uncertainty-Aware Action Advising for Deep Reinforcement Learning Agents
F. L. Da Silva, P. Hernandez-Leal, B. Kartal, and M. E. Taylor. Association for the Advancement of Artificial Intelligence (AAAI), 2020
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Maximum Entropy Monte-Carlo Planning
Maximum Entropy Monte-Carlo Planning
C. Xiao, R. Huang, J. Mei, D. Schuurmans, and M. Müller. The Conference and Workshop on Neural Information Processing Systems (NeurIPS), 2019
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Towers of Saliency: A Reinforcement Learning Visualization Using Immersive Environments
Towers of Saliency: A Reinforcement Learning Visualization Using Immersive Environments
N. Douglas, D. Yim, B. Kartal, P. Hernandez-Leal, M. E. Taylor, and F. Maurer. International Conference on Interactive Surfaces and Spaces (ISS), 2019
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A Survey and Critique of Multiagent Deep Reinforcement Learning
A Survey and Critique of Multiagent Deep Reinforcement Learning
P. Hernandez-Leal, B. Kartal, and M. E. Taylor. International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2019
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On Principled Entropy Exploration in Policy Optimization
On Principled Entropy Exploration in Policy Optimization
*J. Mei, *C. Xiao, R. Huang, D. Schuurmans, and M. Müller. International Joint Conference on Artificial Intelligence (IJCAI), 2019
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On Hard Exploration for Reinforcement Learning: a Case Study in Pommerman
On Hard Exploration for Reinforcement Learning: a Case Study in Pommerman
C. Gao, B. Kartal, P. Hernandez-Leal, and M. E. Taylor. AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2019
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Action Guidance with MCTS for Deep Reinforcement Learning
Action Guidance with MCTS for Deep Reinforcement Learning
*B. Kartal, *P. Hernandez-Leal, and M. E. Taylor. AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2019
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Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning
Terminal Prediction as an Auxiliary Task for Deep Reinforcement Learning
*B. Kartal, *P. Hernandez-Leal, and M. E. Taylor. AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2019
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Agent Modeling as Auxiliary Task for Deep Reinforcement Learning
Agent Modeling as Auxiliary Task for Deep Reinforcement Learning
*B. Kartal, *P. Hernandez-Leal, and M. E. Taylor. AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), 2019
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