Learning Closed-Loop Parametric Nash Equilibria of Multi-Agent Collaborative Field Coverage

14 March 2025

Papers citing "Learning Closed-Loop Parametric Nash Equilibria of Multi-Agent Collaborative Field Coverage"

11 / 11 papers shown

Title
Distributed Multi-agent Interaction Generation with Imagined Potential Games Lingfeng Sun Pin-Yun Hung Changhao Wang Masayoshi Tomizuka Zhuo Xu 57 9 0 02 Oct 2023
Distributed Potential iLQR: Scalable Game-Theoretic Trajectory Planning for Multi-Agent Interactions Zach Williams Jushan Chen Negar Mehr 65 18 0 08 Mar 2023
Breaking the Curse of Multiagents in a Large State Space: RL in Markov Games with Independent Linear Function Approximation Qiwen Cui Kai Zhang S. Du 82 23 0 07 Feb 2023
Efficient Constrained Multi-Agent Trajectory Optimization using Dynamic Potential Games Maulik Bhatt Yixuan Jia Negar Mehr 57 14 0 17 Jun 2022
Potential iLQR: A Potential-Minimizing Controller for Planning Multi-Agent Interactive Trajectories Talha Kavuncu Ayberk Yaraneri Negar Mehr 44 32 0 10 Jul 2021
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms Kai Zhang Zhuoran Yang Tamer Basar 221 1,226 0 24 Nov 2019
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents Kai Zhang Zhuoran Yang Han Liu Tong Zhang Tamer Basar 110 591 0 23 Feb 2018
Learning Parametric Closed-Loop Policies for Markov Potential Games Sergio Valcarcel Macua Javier Zazo S. Zazo 74 46 0 03 Feb 2018
Learning to Communicate with Deep Multi-Agent Reinforcement Learning Jakob N. Foerster Yannis Assael Nando de Freitas Shimon Whiteson 165 1,614 0 21 May 2016
Decentralized Q-Learning for Stochastic Teams and Games Gürdal Arslan S. Yüksel 72 114 0 25 Jun 2015
Playing Atari with Deep Reinforcement Learning Volodymyr Mnih Koray Kavukcuoglu David Silver Alex Graves Ioannis Antonoglou Daan Wierstra Martin Riedmiller 132 12,272 0 19 Dec 2013