Social knowledge is one of the key aspects of MAS in order to face complex problems in dynamical environments. However, it is usually incorporated without specific support on behalf of the platform and that does not let agents take all…

Diagnosis is an important process in patient care. A suitable diagnosis helps a physician determine a precise treatment. Physicians also have a tendency to seek collaboration from other colleagues and expert systems for better confidence in their decision. The sources…

Multi-agent systems (MAS) offer an approach to solve complex problems where data and control are inherently distributed among several agents. Normally, agents have to cope with conflicts based on inconsistent knowledge which arise when they exchange information. A relative common…

In this work we present a reactive autonomous robot navigation system based only on omnidirectional vision. It does not rely on any prior knowledge about the environment apart from assuming a structured one, like indoor corridors or outdoor avenues. The…

MACSimJX provides the means for advanced modelling and development of multiagent driven control systems. This is achieved by drawing together two modelling tools used extensively in their respective communities. These are Simulink, a tool used for control systems development and…

In this article we describe a novel algorithm that allows fast and continuous learning on a physical robot working in a real environment. The learning process is never stopped and new knowledge gained from robot-environment interactions can be incorporated into…

PET is a nuclear medical examination which constructs a three-dimensional image of metabolism inside the body; in this article is particular, images are taken from the brain. The high complexity inherent to the interpretation of the brain images makes that…

This article overviews the concepts of distributed intelligence, outlining the motivations for studying this field of research. First, common systems of distributed intelligence are classified based upon the types of interactions exhibited, since the type of interaction has relevance to…

The ability of building robust semantic space representations of environments is crucial for the development of truly autonomous robots. This task, inherently connected with cognition, is traditionally achieved by training the robot with a supervised learning phase. We argue that…

In this paper we introduce a probabilistic approach to support visual supervision and gesture recognition. Task knowledge is both of geometric and visual nature and it is encoded in parametric eigenspaces. Learning processes for compute modal subspaces (eigenspaces) are the…