Shuang Ao, Tianyi Zhou, Guodong Long and

Qinghua Lu, Liming Zhu, Jing Jiang

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reinforcement learning and planning

Zhenyu Shi*, Runsheng Yu*, Xinrun Wang* and

Rundong Wang, Youzhi Zhang, Hanjiang Lai, Bo An

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Multi-Agent Deep Reinforcement Learning, Deep Reinforcement Learning, Leader–Follower Markov Game, Expensive Coordination

Georgios Birmpas, Jiarui Gan, Alexandros Hollender and

Francisco Marmolejo, Ninad Rajgopal, Alexandros Voudouris

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Andrea Micheli, Alessandro Valentini

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Tijana Zrnic, Eric Mazumdar, Shankar Sastry, Michael Jordan

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machine learning

Karl Pertsch, Oleh Rybkin, Frederik Ebert and

Shenghao Zhou, Dinesh Jayaraman, Chelsea Finn, Sergey Levine

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Applications -> Robotics; Reinforcement Learning and Planning -> Exploration; Reinforcement Learning and Planning -> Reinforcem, Algorithms -> Multitask and Transfer Learning

Tom Silver, Rohan Chitnis, Aidan Curtis and

Joshua B. Tenenbaum, Tomás Lozano-Pérez, Leslie Pack Kaelbling

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Vivek Veeriah, Tom Zahavy, Matteo Hessel and

Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh

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deep learning, reinforcement learning and planning

Mingde Zhao, Zhen Liu, Sitao Luan and

Shuyuan Zhang, Doina Precup, Yoshua Bengio

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deep learning, reinforcement learning and planning

Alexander Li, Carlos Florensa, Ignasi Clavera, Pieter Abbeel

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Hierarchical Reinforcement Learning, Transfer, Skill Discovery

Christopher Hoang, Sungryull Sohn, Jongwook Choi and

Wilka Carvalho, Honglak Lee

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reinforcement learning and planning, graph learning

Andreea-Ioana Deac, Petar Veličković, Ognjen Milinkovic and

Pierre-Luc Bacon, Jian Tang, Mladen Nikolic

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deep learning, reinforcement learning and planning, self-supervised learning, generative model, graph learning

Dilip Arumugam, Benjamin Van Roy

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Reinforcement Learning and Planning, Bandits

Victoria Krakovna, Laurent Orseau, Richard Ngo and

Miljan Martic, Shane Legg

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Marlesson R. O. Santana, Luckeciano C. Melo, Fernando H. F. Camargo and

Bruno Brandão, Anderson Soares, Renan M. Oliveira, Sandor Caetano

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contextual bandits, hierarchical recommender systems, options framework, reinforcement learning

Dor Atzmon, Roni Stern, Ariel Felner and

Nathan R. Sturtevant, Sven Koenig

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Probabilistic, Robust, Multi-Agent Path Finding, MAPF, Collisions, Conflicts, Planning

Kishor Jothimurugan, Osbert Bastani, Rajeev Alur

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Matteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola Gatti

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Lunjun Zhang, Ge Yang, Bradly Stadie

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Applications, Computer Vision, Algorithms, Classification; Applications, Computational Social Science; Applications, Visual Scene Analysis and Interpret, Reinforcement Learning and Planning, Deep RL

Kevin Lu, Aditya Grover, Pieter Abbeel, Igor Mordatch

Keywords Abstract Paper

reinforcement learning, lifelong, reset-free

Tianyu Li, Bogdan Mazoure, Doina Precup, Guillaume Rabusseau

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William Shen, Felipe Trevizan, Sylvie Thiébaux

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classical planning, learning heuristics, deep learning

Guillem Francès, Blai Bonet, Hector Geffner

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Songtao Lu, Kaiqing Zhang, Tianyi Chen and

Tamer Başar, Lior Horesh

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Rostislav Horčík, Daniel Fišer

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Lei Chen, Fajie Yuan, Jiaxi Yang and

Xiang Ao, Chengming Li, Min Yang

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Panteha Naderian, Gabriel Loaiza-Ganem, Harry Braviner and

Anthony Caterini, Jesse C Cresswell, Tong Li, Animesh Garg

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reinforcement learning, goal reaching, Q-learning

Kishor Jothimurugan, Suguman Bansal, Osbert Bastani, Rajeev Alur

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deep learning, reinforcement learning and planning, graph learning

Filippos Christianos, Georgios Papoudakis, Arrasy Rahman, Stefano V. Albrecht

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Reinforcement Learning and Planning

Yinlam Chow, Ofir Nachum, Aleksandra Faust and

Edgar Dueñez-Guzman, Mohammad Ghavamzadeh

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Rohan Chitnis, Tom Silver, Beomjoon Kim and

Leslie Kaelbling, Tomas Lozano-Perez

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Zaheen Ahmad, Levi Lelis, Michael Bowling

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Optimization -> Non-Convex Optimization; Theory -> Computational Complexity; Theory -> Learning Theory, Deep Learning -> Optimization for Deep Networks

Maximilian Igl, Andrew Gambardella, Jinke He and

Nantas Nardelli, N Siddharth, Wendelin Boehmer, Shimon Whiteson

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Yichen Yang, Jeevana Priya Inala, Osbert Bastani and

Yewen Pu, Armando Solar-Lezama, Martin Rinard

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reinforcement learning and planning, generative model

Genevieve Flaspohler, Nicholas Roy, John Fisher III

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Shashank Shekhar, Ronen I. Brafman, Guy Shani

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Devendra Singh Chaplot, Deepak Pathak, Jitendra Malik

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Reinforcement Learning and Planning

Anirudh Goyal, Shagun Sodhani, Jonathan Binas and

Xue Bin Peng, Sergey Levine, Yoshua Bengio

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Reinforcement Learning, Variational Information Bottleneck, Learning primitives

Ming Yin, Yu Bai, Yu-Xiang Wang

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Arman Adibi, Aryan Mokhtari, Hamed Hassani

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