Our group is working now on the following main areas:
Multi-agent systems paradigm is a growing interest area in AI. It is due to its application to complex problem resolution, where classical techniques falls in the obtention of a satisfactory solution. Multi-agent systems (MAS) face up to the necessity of communication and collaboration among autonomous agents (entities which behaviour is guided by themselves).
Applications:
Within the MAS research line, the GTI-IA is working in the following areas:
It specifies how the MAS can be decomponed into a set of independent modules (agents) and how these agents can interact. The total set of agents and interactions must provide a reponse to the problem of determining actions and future internal states from the current world situation and the internal state of each agent.
Principles and basic lessons from Software Engineering and Knowledge Engineering must be applied to development and implementation of MAS. Currently, almost all agent-based software is developed by following non-rigurous, design methodologies and using limited specifications dependieng on the design requirements. Some considered topics in this area are:
Modular and open design of intelligent distributed systems make the resulting system to be composed of multiples autonomous intelligent agents. Each agent has different capabilities. Efficient use of such agents in distrubuted problem-solving requires mechanisms for controlling and coordinating the behaviour of individual agents. The final goal is the fullfilment of the whole system goal. The interest is focused on the social behaviour of intelligent entities. It deals with the investigation of behaviour models, co-operation strategies, negotiation models, etc.
Holonic systems are intelligent production systems, formed by autonomous and auto-configurable units, called holons, which collaborate to reach the global goal of the production system. The main purpose of holonic systems is to obtain stability in the presence of disturbs, adaptability and flexibility before changes and efficient use of available resources.
Real-Time Artificial Intelligence is a discipline that incorporates problem-solving techniques used in AI environments with real-time constraints. These environments need a valid response in bounded time intervals for guaranteing the correct working of the system. Clasical AI techniques must be adapted to be applied in such environments.
Applications:
Autonomous systems in robotics are designed to realise tasks without the supervision of human controllers. There are several advantages: to minimise the controller fatigue, to minimise the dangerous woks risks, to minimise the operational costs and to improve the products and operations quality control.
Applications:
A Real-Time system is a computing system in which the accuracy of the response depends on not only the logical accuracy, but also the time instant in which it is obtained.
Applications: