We propose a new set of criteria for learning algorithms in multi-agent systems, one that is more stringent and (we argue) better justified than previous proposed criteria. Our cr...
Previous work in knowledge transfer in machine learning has been restricted to tasks in a single domain. However, evidence from psychology and neuroscience suggests that humans ar...
As the complexity and application scope of agent-based systems increases, the requirements placed on Agent Communication Languages have also increased with it. Currently-available...
How should a reinforcement learning agent act if its sole purpose is to efficiently learn an optimal policy for later use? In other words, how should it explore, to be able to exp...
We present here a framework together with a set of paradigms for mobile agent based active monitoring of network systems. In our framework mobile agents are used to perform remote...