This volume contains papers read at the 7th International Workshop entitled "Intelligent Agents: Decision-Support and Planning", Udine, Italy, Sep 30th - Oct 2nd, 2004. All papers were reviewed after they were presented, and revised for final publication. As its preceding ones, this workshop took place under the auspices of the International School for the Synthesis of Expert Knowledge (ISSEK) and was held in the picturesque Palazzo del Torso of the Centre International des Sciences Mecaniques (CISM), Udine, see picture below. CISM location " Palazzo del Torso " The workshop was jointly organised by Prof. G. Delia Riccia (University of Udine), Dr. D. Dubois ( CNRS and University of Toulouse III), Prof. R. Kruse (University of Magdeburg), and Prof. H .- J. Lenz (Free University Berlin). As the workshop was an invitational one, there was no need for a call for contributed papers. Contrarily, the four organisers recruited research workers from Europe who have had an impact in the last decade on "Intelligent Agents: Decision-Support and Planning".

This work is a collection of front-end research papers on data fusion and perceptions. Authors are leading European experts of Artificial Intelligence, Mathematical Statistics and/or Machine Learning. Area overlaps with Intelligent Data Analysis, which aims to unscramble latent structures in collected data: Statistical Learning, Model Selection, Information Fusion, Soccer Robots, Fuzzy Quantifiers, Emotions and Artifacts.

The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing. Data Mining focuses on unscrambling unknown patterns or structures in very large data sets. Under the headline Discovering Structures in Large Databases the book starts with a unified view on Data Mining and Statistics - A System Point of View. Two special techniques follow: Subgroup Mining, and Data Mining with Possibilistic Graphical Models. Data Fusion and Possibilistic or Fuzzy Data Analysis is the next area of interest. An overview of possibilistic logic, nonmonotonic reasoning and data fusion is given, the coherence problem between data and non-linear fuzzy models is tackled, and outlier detection based on lernaing of fuzzy models is studied. In the domain of Classification and Decomposition adaptive clustering and visualisation of high dimensional data sets is introduced. Finally, in the section Learning and Data Fusion learning of special multi-agents of virtual soccer is considered. The last topic is on data fusion based on stochastic models.

The contents of these proceedings reflect the intention of the organizers of the workshop to bring together scientists and engineers having a strong interest in interdisciplinary work in the fields of computer science, mathematics and applied statistics. Results of this collaboration are illustrated in problems dealing with neural nets, statistics and networks, classification and data mining, and (machine) learning.