2026
Think How Your Teammates Think: Active Inference Can Benefit Decentralized Execution
AAAI 2026technical
In multi-agent systems, explicit cognition of teammates
5 accepted papers
In multi-agent systems, explicit cognition of teammates
Communication has been widely employed to enhance multi-agent collaboration. Previous research has typically assumed delay-free communication, a strong assumption that is challenging to meet in practice. However, real-world agents suffer from channel delays, receiving messages sent at different time…
Continual Multi-Agent Reinforcement Learning (Co-MARL) requires agents to address catastrophic forgetting issues while learning new coordination policies with the dynamics team. In this paper, we delve into the core of Co-MARL, namely Relation Patterns, which refer to agents’ general understanding o
Vehicle re-identification aims to match vehicles across non-overlapping camera views. Many existing methods extract features from one specific image, and these methods lack view-invariance when comparing vehicles of different orientations. As a result, discriminative parts obscured by viewpoint chan…
In the domain of real-world agents, the application of Reinforcement Learning (RL) remains challenging due to the necessity for safety constraints. Previously, Constrained Reinforcement Learning (CRL) has predominantly focused on on-policy algorithms. Although these algorithms exhibit a degree of ef…