2022/01/08 · In this paper, we propose a multi-agent reinforcement learning algorithm with cognition differences and consistent representation (CDCR). The ...

2022/07/01 · In this paper, we propose a multi-agent reinforcement learning algorithm with cognition differences and consistent representation (CDCR).

Due to the consistency between neighborhood-specific cognitions as well as the difference between agent-specific cognitions, the neighboring agents can achieve ...

Enhancing cooperation by cognition differences and consistent representation in multi-agent reinforc... · Hongwei Ge · Zhixin Ge · Liang Sun · Yuxin Wang.

This work proposes neighborhood cognition consistent deep Q-learning and Actor-Critic to facilitate large-scale multi-agent cooperations and justifies the ...

2024/08/18 · Abstract. The significance of network structures in promot- ing group cooperation within social dilemmas has been widely recognized.

Enhancing cooperation by cognition differences and consistent representation in multi-agent reinforcement learning · Computer Science. Applied Intelligence · 2022.

In cooperative multi-agent reinforcement learn- ing, centralized training with decentralized exe- cution (CTDE) shows great promise for a trade-.

To address this, our study introduces a computational framework based on multi-agent reinforcement learning in the spatial Prisoner's Dilemma game. This ...

By keeping consistent with each other through self-supervised learning and aligning individual goal with that of other agents, each agent forms a consistent ...