Portugal

NIAD&R-LIACC - Artificial Intelligence and Computer Science Laboratory

Membership Details (Research Institute)

Contact:
Member node: 118
Faculdade de Engenharia da Universidade do Porto Rua Dr. Roberto Frias 4200-465 Porto Portugal
Portugal

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Description

NIAD&R, the Distributed Artificial Intelligence Group at LIACC, aims at promoting focused research in the academic environment. We simultaneously aim at i) helping researchers to develop their own thesis, ii) collaborating in contributing for innovative international trends in the autonomous agents research area and iii)trying to influence non-academics through meaningful transference of concepts, models and case studies exemplifying our main ideas in the Software Autonomous Agents field.

Besides the Application oriented work, we have selected three main research lines in the Autonomous Agents field that we believe can be of great importance also in the near future:
- Flexible Tools and trustful Frameworks for agents interaction. We believe that sophistication of autonomous and pro-active agents can only be relevant when people understand and trust the environment in which their procurers (intelligent software agents) perform their activities on their behalf. This is why our research aims at the progressive establishment of largely accepted Electronic Institutions providing, on one hand, all the needed capabilities for fair, however personalized negotiation protocols and agents' coordination and, on the other hand, the capability of guiding, monitoring and providing help for all that is happening during the agents' electronic encounters. We are pursuing this research line mainly in the domain of Virtual Enterprises life cycle.
- Advanced features for Autonomous Agents. A set of essential, intrinsic features are needed for computational agents to show intelligent (sometimes human-like) behaviour. The quest for real learning and flexible adaptation is a difficult one. Due to our current interests, we have elected as our research objective in what this topic is concerned, enhancing agents' on-line (therefore not using traditional off-line examples-based) learning policies. Also in the same line, we are now exploring how "emotion-based" architectures can lead agents to display decision-making capabilities that are not completely under the utility-based function paradigm.
- Multi-Agent coordination and cooperation in dynamic environments. Our aim here is deriving methods and protocols for coordination and cooperation of agent teams that perform complex tasks in dynamic, inaccessible, non-deterministic multi-agent scenarios. Our research is aimed at assembling teams of physical (robotic) or virtual (software) agents that perform complex tasks in real world or simulated environments. Research is focused on cooperation protocols and models for cooperation, teamwork and coalition formation methods, coordination languages and systems and implementation of multi-agent systems paying specific attention to cooperation and coordination methods.

A fourth important issue we are involved with is Agents and Multi-agent systems applications. We are currently trying to apply agent-based techniques to automatic Virtual Enterprises formation as well as to Electronic Markets frameworks. Electronic Markets for Electrical Energy is one of our applications in progress. Automatic agent-mediated e-Brokering for the Insurance domain, is another problem we have modeled, developed and proposed an interesting (feasible) solution to. Presentations to potentially interested Software houses are now being done. Multi-Agent learning for improving road traffic control is another field of application. Learning to model data communication networks' messages congestion and applying "emotion-based" agent architectures to fire combat simulation are two recent applications we have been developing.

We may summarize the scope of our research efforts by explicitly emphasising the following topics: Adaptive, multi-attribute agents negotiation leading to contracts; emotion-like agents architectures for group behaviour simulation; learning capabilities and decision-making in the Multi-Agent Systems context; Agent-based teams coordination.

We also have been, for the last years, present in some of the major international agent related conferences Program Committees (AAMAS- Autonomous Agents and Multiagent Systems, ECAI- European Conference on Artificial Intelligence, Autonomous Agents-AA, CIA-Coopertive Information Agents Workshop, IEEE International Conference on Web Intelligence, EUMAS- European Conference on Multi-Agent Systems) as well as ICMAS, MAAMAW, IEEE International Conference on Concurrent Engineering, EPIA- Portuguese AI Meeting, SBIA- Brasilian AI Symposium. We have been co-founders of the European Network of Excellence AgentLink, now AgentLink III. We have been active, since the beginning, in both the AMEC(Agent-mediated Electronic Commerce) and ALAD (Adaptive and Learning Agents) Special Interest Groups, organising special sessions and presenting our current research. We also have contributed to the book already published by AMEC SIG. We have also successfully participated in the major robotic soccer (RoboCup) competitions. In previous years, we have won one RoboCup championship (simulation league - Melbourne 2000), two European championships (simulation league - Amsterdam 2000 and Paderborn 2001) and one RoboCup world coach competition (Fukuoka, 2002), and got the second place in 2003 (Pisa). We are currently supervising students both coming from foreign Universities (Brasil) and staying at foreign Universities and Laboratories (Centre for Biomedical E

Conference or Workshop Item

Castro, Antonio and Oliveira, Eugenio (2005) A Multi-Agent System for Intelligent Monitoring of Airline Operations. In: 3rd European Workshop on Multiagent Systems 2005, 07-08 Dec 2005, Brussels, Belgium.

Course

[Course] Oliveira, Eugenio (2005) Multiagent Systems.

Thesis

Alves, A.A. (2004) Internet Traffic Engineering: An Artificial Intelligence Approach. Masters thesis, University of Porto.

Alves, A. (2004) Internet Traffic Engineering: An Artificial Intelligence Approach. Masters thesis, University of Porto.

This list was generated on Mon Sep 10 16:39:28 BST 2007.

   

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