This paper presents a self-organizing cognitive architecture, known as TD-FALCON, that learns to function through its interaction with the environment. TD-FALCON learns the value ...
We consider the problem of how to design large decentralized multiagent systems (MAS’s) in an automated fashion, with little or no hand-tuning. Our approach has each agent run a...
Multi-Agent Agreement problems (MAP) - the ability of a population of agents to search out and converge on a common state - are central issues in many multi-agent settings, from d...
Multi agent learning systems pose an interesting set of problems: in large environments agents may develop localised behaviour patterns that are not necessarily optimal; in a pure...
In this paper, we will consider the alignment of heterogeneous ontologies in multi agent systems. We will start from the idea that each individual agent is specialized in solving ...
Jurriaan van Diggelen, Robbert-Jan Beun, Frank Dig...