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
We study a model of observational learning in social networks in the presence of uncertainty about agents' type distributions. Each individual receives a private noisy signal ...
Daron Acemoglu, Munther A. Dahleh, Asuman E. Ozdag...
The paper presents the Multi Agent System (MAS) designed for the large scale parallel computations. The special kind of diffusionbased scheduling enables to decompose and allocate...
Maciej Smolka, Piotr Uhruski, Robert Schaefer, Mar...
Mobile agent technology is an emerging technology that allows easier design, implementation, and maintenance of distributed systems. Mobility enables agents to reduce network load,...
This paper discusses the use of simulation in a new context. Most often QUEST is viewed as a stand-alone simulation tool to analyze and understand shop floor behavior. It has rare...