Developing agent applications is a complex and difficult task due to a variety of reasons. One key aspect making multi-agent systems more complicated than traditional applications ...
Learning to converge to an efficient, i.e., Pareto-optimal Nash equilibrium of the repeated game is an open problem in multiagent learning. Our goal is to facilitate the learning ...
We have developed and integrated software agents with two educational groupware systems (TeamWave Workplace and FLE), using evolutionary prototyping and empiricalbased design as d...
We present a low cost wireless microsensor node architecture for distributed computation and sensing in massively distributed embedded systems. Our design focuses on the developme...
Agent-based approaches in application development seem to meet the requirements of adaptability, scalability, decentralization, and flexibility imposed by complex software systems....