Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
In this paper, an internal design model called FunState (functions driven by state machines) is presented that enables the representation of different types of system components a...
This paper describes an algorithm, called CQ-learning, which learns to adapt the state representation for multi-agent systems in order to coordinate with other agents. We propose ...
The iterated prisoner’s dilemma is a widely used computational model of cooperation and conflict. Many studies report emergent cooperation in populations of agents trained to p...
This paper describes a novel and competitive complete conformant planner. Key to the enhanced performance is an efficient encoding of belief states as disjunctive normal form form...