Abstract. Both symbolic knowledge representation systems and artificial neural networks play a significant role in Artificial Intelligence. A recent trend in the field aims at ...
Ilianna Kollia, Nikos Simou, Giorgos B. Stamou, An...
s, covering different levels of abstraction over the information exchanged. As the protocol is layered, we can discuss interaction in terms of different levels of granularity, bett...
David J. Duke, David A. Duce, Philip J. Barnard, J...
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
In this paper, we model multi-agent events in terms of a temporally varying sequence of sub-events, and propose a novel approach for learning, detecting and representing events in...