In this article we describe a set of scalable techniques for learning the behavior of a group of agents in a collaborative multiagent setting. As a basis we use the framework of c...
Many algorithms such as Q-learning successfully address reinforcement learning in single-agent multi-time-step problems. In addition there are methods that address reinforcement l...
In many different applications on the Web, distributed agents would like to discover and access high quality information sources. This is a challenging problem since an agent does...
We consider multi-agent systems whose agents compete for resources by striving to be in the minority group. The agents adapt to the environment by reinforcement learning of the pr...
Multi-agent research often borrows from biology, where remarkable examples of collective intelligence may be found. One interesting example is ant colonies’ use of pheromones as...