Abstract. This paper presents a formal framework within which autonomous agents can dynamically select and apply different mechanisms to coordinate their interactions with one ano...
Rachel A. Bourne, Karen Shoop, Nicholas R. Jenning...
Systems that learn from examples often express the learned concept in the form of a disjunctive description. Disjuncts that correctly classify few training examples are known as s...
We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selectio...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian ...
Abstract. In this paper we focus on explaining to humans the behavior of autonomous agents, i.e., explainable agents. Explainable agents are useful for many reasons including scena...
Joost Broekens, Maaike Harbers, Koen V. Hindriks, ...
A multi-agent system can be analyzed and specified as an organization consisting of roles and their relations. The performance of an organization depends on many factors among whi...
Davide Grossi, Frank Dignum, Virginia Dignum, Mehd...