Multi-agent learning is a crucial method to control or find solutions for systems, in which more than one entity needs to be adaptive. In today's interconnected world, such s...
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
We propose Path Disruption Games (PDGs), which consider collaboration between agents attempting stop an adversary from travelling from a source node to a target node in a graph. P...
This paper concerns the problem of agent trust in an electronic market place. We maintain that agent trust involves making decisions under uncertainty and therefore the phenomenon...
Speakers in dialogue tend to adapt to each other by starting to use similar lexical items, syntactic structures, or gestures. This behaviour, called alignment, may serve important...