Learning general truths from the observation of simple domains and, further, learning how to use this knowledge are essential capabilities for any intelligent agent to understand ...
Paulo Santos, Derek R. Magee, Anthony G. Cohn, Dav...
This paper presents a novel approach to clustering using an accuracy-based Learning Classifier System. Our approach achieves this by exploiting the generalization mechanisms inher...
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 ...
In multi-agent planning environments, action models for each agent must be given as input. However, creating such action models by hand is difficult and time-consuming, because i...
Reasoning about the past is of fundamental importance in several applications in computer science and artificial intelligence, including reactive systems and planning. In this pa...