This paper investigates whether replacing non-modular artificial neural network brains of visual agents with modular brains improves their ability to solve difficult tasks, specif...
Ehud Schlessinger, Peter J. Bentley, R. Beau Lotto
This paper presents the dynamics of multi-agent reinforcement learning in multiple state problems. We extend previous work that formally modelled the relation between reinforcemen...
Recognizing team actions in the behavior of embodied agents has many practical applications and had seen significant progress in recent years. One approach with proven results is ...
Abstract. In open and heterogeneous environments offered by the Internet, where agents are designed by different vendors, the development of standards for agent communication nee...
In this paper we: introduce EMADS, the Extendible Multi-Agent Data mining System, to support the dynamic creation of communities of data mining agents; explore the capabilities of ...