Introduction

This page is dedicated to the study of what happens when agents (i.e. pro-active, goal-driven, selfish, independent software/hardware constructs) start to learn about each other, especially if they do so in order to gain a competitive advantage over the other agents. This scenario (which I believe we will be seeing a lot more of in the near future) gives rise to interesting questions/phenomena:

• Sometimes, it is better for agents not to learn about others, not so at other times. When is learning useful? What kind of learning?
• If I think about what you think about what I think....When do I stop?
• Having agents that can "watch out for themselves" eliminates the need of a big-brother type approach, giving rise to a more robust distributed system.
• If we allow the agents to evolve, we have a very complicated CAS (Complex Adaptive System). Will the agents' learning capabilities reach a stable level, balancing the computational costs with the gains of learning?

NOTE: A good place to start is at www.MultiAgent.com.