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Multi-robot inverse reinforcement learning under occlusion with estimation of state transitions

  • Published:2018-10 Issue: Volume:263 Page:46-73
  • ISSN:0004-3702
  • Container-title:Artificial Intelligence
  • language:en
  • Short-container-title:Artificial Intelligence

Author:

Bogert KennethORCID,Doshi Prashant

Funder

NSF

ONR

Toyota Research Institute of North America

Publisher

Elsevier BV

Subject

Artificial Intelligence,Linguistics and Language,Language and Linguistics

Reference37 articles.

1. Apprenticeship learning via inverse reinforcement learning;Abbeel,2004

2. Multi-robot perimeter patrol in adversarial settings;Agmon,2008

3. A survey of robot learning from demonstration;Argall;Robot. Auton. Syst.,2009

4. The complexity of multi-agent plan recognition;Banerjee;Auton. Agents Multi-Agent Syst.,2015

5. Estimation of state probabilities using the maximum entropy principle;Bard;IBM J. Res. Dev.,1980

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1. Security Reinforcement Learning Guided by Finite Deterministic Automata;2024 9th International Conference on Computer and Communication Systems (ICCCS);2024-04-19

2. Collective Anomaly Perception During Multi-Robot Patrol: Constrained Interactions Can Promote Accurate Consensus;Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing;2024-04-08

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4. LEMURS: Learning Distributed Multi-Robot Interactions;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

5. Inverse Reinforcement Learning as the Algorithmic Basis for Theory of Mind: Current Methods and Open Problems;Algorithms;2023-01-19
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