Search Results for author: Jingxiao Chen

Found 7 papers, 4 papers with code

Looking Ahead to Avoid Being Late: Solving Hard-Constrained Traveling Salesman Problem

no code implementations8 Mar 2024 Jingxiao Chen, Ziqin Gong, Minghuan Liu, Jun Wang, Yong Yu, Weinan Zhang

To overcome this problem and to have an effective solution against hard constraints, we proposed a novel learning-based method that uses looking-ahead information as the feature to improve the legality of TSP with Time Windows (TSPTW) solutions.

Traveling Salesman Problem

Offline Fictitious Self-Play for Competitive Games

no code implementations29 Feb 2024 Jingxiao Chen, Weiji Xie, Weinan Zhang, Yong Yu, Ying Wen

Firstly, unaware of the game structure, it is impossible to interact with the opponents and conduct a major learning paradigm, self-play, for competitive games.

Offline RL Reinforcement Learning (RL)

ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination

1 code implementation8 Oct 2023 Xihuai Wang, Shao Zhang, WenHao Zhang, Wentao Dong, Jingxiao Chen, Ying Wen, Weinan Zhang

ZSC-Eval consists of: 1) Generation of evaluation partner candidates through behavior-preferring rewards to approximate deployment-time partners' distribution; 2) Selection of evaluation partners by Best-Response Diversity (BR-Div); 3) Measurement of generalization performance with various evaluation partners via the Best-Response Proximity (BR-Prox) metric.

Multi-agent Reinforcement Learning

On Realization of Intelligent Decision-Making in the Real World: A Foundation Decision Model Perspective

1 code implementation24 Dec 2022 Ying Wen, Ziyu Wan, Ming Zhou, Shufang Hou, Zhe Cao, Chenyang Le, Jingxiao Chen, Zheng Tian, Weinan Zhang, Jun Wang

The pervasive uncertainty and dynamic nature of real-world environments present significant challenges for the widespread implementation of machine-driven Intelligent Decision-Making (IDM) systems.

Decision Making Image Captioning +2

Efficient Policy Space Response Oracles

no code implementations28 Jan 2022 Ming Zhou, Jingxiao Chen, Ying Wen, Weinan Zhang, Yaodong Yang, Yong Yu, Jun Wang

Policy Space Response Oracle methods (PSRO) provide a general solution to learn Nash equilibrium in two-player zero-sum games but suffer from two drawbacks: (1) the computation inefficiency due to the need for consistent meta-game evaluation via simulations, and (2) the exploration inefficiency due to finding the best response against a fixed meta-strategy at every epoch.

Efficient Exploration

Improving Dialog Systems for Negotiation with Personality Modeling

1 code implementation ACL 2021 Runzhe Yang, Jingxiao Chen, Karthik Narasimhan

In this paper, we explore the ability to model and infer personality types of opponents, predict their responses, and use this information to adapt a dialog agent's high-level strategy in negotiation tasks.

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