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
In this paper, we present a new trajectory planning algorithm for virtual humans. Our approach focuses on implicit cooperation between multiple virtual agents in order to share th...
Increasing teamwork between agents typically increases the performance of a multi-agent system, at the cost of increased communication and higher computational complexity. This wo...
Matthew E. Taylor, Manish Jain, Yanquin Jin, Makot...
The primary target of this work is human-robot collaboration, especially for service robots in complicated application scenarios. Three assumptions and four requirements are ident...
Xiaoping Chen, Jianmin Ji, Jiehui Jiang, Guoqiang ...
We consider collusion in multi-unit auctions where the allocation and payments are determined using the VCG mechanism. We show how collusion can increase the utility of the collud...