Abstract. Autonomous learning systems of significant complexity often consist of several interacting modules or agents. These modules collaborate to produce a system which, when vi...
Solutions to complex tasks often require the cooperation of multiple robots, however, developing multi-robot policies can present many challenges. In this work, we introduce teach...
This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of...
Matrix factorization is a fundamental technique in machine learning that is applicable to collaborative filtering, information retrieval and many other areas. In collaborative fil...
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...