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Workshop
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Rewards Encoding Environment Dynamics Improves Preference-based Reinforcement Learning
Katherine Metcalf · Miguel Sarabia · Barry-John Theobald
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Workshop
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Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models
Yi Liu · Gaurav Datta · Ellen Novoseller · Daniel Brown
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Workshop
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PD-MORL: Preference-Driven Multi-Objective Reinforcement Learning Algorithm
Toygun Basaklar · Suat Gumussoy · Umit Ogras
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Workshop
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Towards customizable reinforcement learning agents: Enabling preference specification through online vocabulary expansion
Utkarsh Soni · Sarath Sreedharan · Mudit Verma · Lin Guan · Matthew Marquez · Subbarao Kambhampati
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Poster
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Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation
Zhizhou Ren · Anji Liu · Yitao Liang · Jian Peng · Jianzhu Ma
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Poster
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Meta-Reward-Net: Implicitly Differentiable Reward Learning for Preference-based Reinforcement Learning
Runze Liu · Fengshuo Bai · Yali Du · Yaodong Yang
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Affinity Workshop
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Modelling non-reinforced preferences using selective attention
Noor Sajid · Panagiotis Tigas · Zafeirios Fountas · Qinghai Guo · Alexey Zakharov · Lancelot Da Costa
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Workshop
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Memory-Efficient Reinforcement Learning with Priority based on Surprise and On-policyness
Ryosuke Unno · Yoshimasa Tsuruoka
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Poster
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I2Q: A Fully Decentralized Q-Learning Algorithm
Jiechuan Jiang · Zongqing Lu
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Workshop
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Meta-learning of Black-box Solvers Using Deep Reinforcement Learning
Cedric Malherbe · Aladin Virmaux · Ludovic Dos Santos · Sofian Chaybouti
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Poster
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Mildly Conservative Q-Learning for Offline Reinforcement Learning
Jiafei Lyu · Xiaoteng Ma · Xiu Li · Zongqing Lu
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Poster
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Multiagent Q-learning with Sub-Team Coordination
Wenhan Huang · Kai Li · Kun Shao · Tianze Zhou · Matthew Taylor · Jun Luo · Dongge Wang · Hangyu Mao · Jianye Hao · Jun Wang · Xiaotie Deng
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