Learning to Play Trajectory Games Against Opponents With Unknown Objectives-Reference-Cited by-同舟云学术

Learning to Play Trajectory Games Against Opponents With Unknown Objectives

Published:2023-07 Issue:7 Volume:8 Page:4139-4146
ISSN:2377-3766
Container-title:IEEE Robotics and Automation Letters
language:
Short-container-title:IEEE Robot. Autom. Lett.

Author:

Liu Xinjie¹^ORCID,Peters Lasse¹^ORCID,Alonso-Mora Javier¹^ORCID

Affiliation:

1. Department of Cognitive Robotics (CoR), Delft University of Technology, Delft, The Netherlands

Funder

European Union through ERC, INTERACT

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/7083369/10128766/10137879.pdf?arnumber=10137879

Reference30 articles.

1. Learning Game-Theoretic Models of Multiagent Trajectories Using Implicit Layers

2. Inferring Objectives in Continuous Dynamic Games from Noise-Corrupted Partial State Observations

3. Where to go Next: Learning a Subgoal Recommendation Policy for Navigation in Dynamic Environments

4. Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning

5. A stable tracking control method for an autonomous mobile robot

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