Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
The synthesis of facial expression with control of intensity and personal styles is important in intelligent and affective human-computer interaction, especially in face-to-face i...
Chan-Su Lee, Ahmed M. Elgammal, Dimitris N. Metaxa...
Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Collaboration between peers is an important aspect of the learning process and can considerably augment learning in studying complex domains. To ensure that peer collaboration occ...
In this paper, we study phase transition behavior emerging from the interactions among multiple agents in the presence of noise. We propose a simple discrete-time model in which a...