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Influence-based Decision-making in Uncertain Environments

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Publications

Influence-Augmented Online Planning for Complex Environments

Author(s): He, Jinke; Suau, Miguel; Oliehoek, Frans A.
Published in: Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 33, 2020
Publisher: Curran Associates, Inc.

Influence-aware Memory Architectures for Deep Reinforcement Learning

Author(s): Suau, Miguel; He, Jinke; Congeduti, Elena; Starre, Rolf A. N.; Czechowski, Aleksander; Oliehoek, Frans A.
Published in: NeurIPS'20 Workshop on Deep Reinforcement Learning, 2020
Publisher: arxiv

Beyond Local Nash Equilibria for Adversarial Networks

Author(s): Oliehoek, Frans A; Savani, Rahul; Gallego, Jose; Pol, Elise van der; Groß, Roderich
Published in: Benelearn 2018 Pre-proceedings, 2018
Publisher: BNAIC

Bayesian Reinforcement Learning in Factored POMDPs

Author(s): Katt, Sammie; Oliehoek, Frans; Amato, Christopher
Published in: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019
Publisher: International Foundation for Autonomous Agents and Multiagent Systems

The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning

Author(s): Castellini, Jacopo; Oliehoek, Frans A.; Savani, Rahul; Whiteson, Shimon
Published in: Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019, Page(s) 1862-1864, ISBN 978-1-4503-6309-9
Publisher: International Foundation for Autonomous Agents and Multiagent Systems

Interactive Learning and Decision Making: Foundations, Insights & Challenges

Author(s): Frans A. Oliehoek
Published in: Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018, Page(s) 5703-5708, ISBN 9780-999241127
Publisher: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2018/813

Plannable Approximations to MDP Homomorphisms: Equivariance under Actions

Author(s): van der Pol, Elise; Kipf, Thomas; Oliehoek, Frans A.; Welling, Max
Published in: Proceedings of the Nineteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2020, Page(s) 1431--1439, ISBN 9781450375184
Publisher: International Foundation for Autonomous Agents and Multiagent Systems

Bayesian Reinforcement Learning in Factored POMDPs

Author(s): Katt, Sammie; Oliehoek, Frans; Amato, Christopher
Published in: Proceedings of the Eighteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2019, Page(s) 7-15, ISBN 978-1-4503-6309-9
Publisher: International Foundation for Autonomous Agents and Multiagent Systems

Decentralized MCTS via Learned Teammate Models

Author(s): Aleksander Czechowski, Frans A. Oliehoek
Published in: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020, Page(s) 81-88, ISBN 978-0-9992411-6-5
Publisher: International Joint Conferences on Artificial Intelligence Organization
DOI: 10.24963/ijcai.2020/12

Maximizing Information Gain in Partially Observable Environments via Prediction Reward

Author(s): Satsangi, Yash; Lim, Sungsu; Whiteson, Shimon; Oliehoek, Frans; White, Martha
Published in: Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems, 2020, Page(s) 1215--1223, ISBN 9781450375184
Publisher: International Foundation for Autonomous Agents and Multiagent Systems

Influence-Based Abstraction in Deep Reinforcement Learning

Author(s): Miguel Suau de Castro, Elena Congeduti, Rolf Starre, Aleksander Czechowski, Frans Oliehoek
Published in: AAMAS Workshop on Adaptive Learning Agents (ALA), 2019
Publisher: https://ala2019.vub.ac.be/

Multi-agent active perception with prediction rewards

Author(s): Lauri, Mikko; Oliehoek, Frans A.
Published in: Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 33, 2020
Publisher: Curran Associates, Inc.

Analog Circuit Design with Dyna-Style Reinforcement Learning

Author(s): Lee, Wook; Oliehoek, Frans A.
Published in: NeurIPS 2020 Workshop: Machine Learning for Engineering Modeling, Simulation, and Design, 1, 2020
Publisher: NeurIPS 2020 Workshop: Machine Learning for Engineering Modeling, Simulation, and Design

The Representational Capacity of Action-Value Networks for Multi-Agent Reinforcement Learning

Author(s): Castellini, Jacopo; Oliehoek, F.A.; Savani, Rahul; Whiteson, Shimon
Published in: arXiv e-prints, 2019
Publisher: arxiv.org

A Sufficient Statistic for Influence in Structured Multiagent Environments

Author(s): Oliehoek, Frans A.; Witwicki, Stefan; Kaelbling, Leslie P.
Published in: arXiv e-prints, 2019
Publisher: arxiv.org

Beyond Local Nash Equilibria for Adversarial Networks

Author(s): Frans A. Oliehoek, Rahul Savani, Jose Gallego, Elise van der Pol, Roderich Groß
Published in: Artificial Intelligence - 30th Benelux Conference, BNAIC 2018, ‘s-Hertogenbosch, The Netherlands, November 8–9, 2018, Revised Selected Papers, 1021, 2019, Page(s) 73-89, ISBN 978-3-030-31977-9
Publisher: Springer International Publishing
DOI: 10.1007/978-3-030-31978-6_7