Logics, Planning, and Theoretical Methods -- On Modalities for Vague Notions -- Towards Polynomial Approximations of Full Propositional Logic -- Using Relevance to Speed Up Inference -- A Non-explosive Treatment of Functional Dependencies Using Rewriting Logic -- Reasoning About Requirements Evolution Using Clustered Belief Revision -- Analysing AI Planning Problems in Linear Logic – A Partial Deduction Approach -- Planning with Abduction: A Logical Framework to Explore Extensions to Classical Planning -- High-Level Robot Programming: An Abductive Approach Using Event Calculus -- Search, Reasoning, and Uncertainty -- Word Equation Systems: The Heuristic Approach -- A Cooperative Framework Based on Local Search and Constraint Programming for Solving Discrete Global Optimisation -- Machine Learned Heuristics to Improve Constraint Satisfaction -- Towards a Natural Way of Reasoning -- Is Plausible Reasoning a Sensible Alternative for Inductive-Statistical Reasoning? -- Paraconsistent Sensitivity Analysis for Bayesian Significance Tests -- Knowledge Representation and Ontologies -- An Ontology for Quantities in Ecology -- Using Color to Help in the Interactive Concept Formation -- Propositional Reasoning for an Embodied Cognitive Model -- A Unified Architecture to Develop Interactive Knowledge Based Systems -- Natural Language Processing -- Evaluation of Methods for Sentence and Lexical Alignment of Brazilian Portuguese and English Parallel Texts -- Applying a Lexical Similarity Measure to Compare Portuguese Term Collections -- Dialog with a Personal Assistant -- Applying Argumentative Zoning in an Automatic Critiquer of Academic Writing -- DiZer: An Automatic Discourse Analyzer for Brazilian Portuguese -- A Comparison of Automatic Summarizers of Texts in Brazilian Portuguese -- Machine Learning, Knowledge Discovery, and Data Mining -- Heuristically Accelerated Q–Learning: A New Approach to Speed Up Reinforcement Learning -- Using Concept Hierarchies in Knowledge Discovery -- A Clustering Method for Symbolic Interval-Type Data Using Adaptive Chebyshev Distances -- An Efficient Clustering Method for High-Dimensional Data Mining -- Learning with Drift Detection -- Learning with Class Skews and Small Disjuncts -- Making Collaborative Group Recommendations Based on Modal Symbolic Data -- Search-Based Class Discretization for Hidden Markov Model for Regression -- SKDQL: A Structured Language to Specify Knowledge Discovery Processes and Queries -- Evolutionary Computation, Artificial Life, and Hybrid Systems -- Symbolic Communication in Artificial Creatures: An Experiment in Artificial Life -- What Makes a Successful Society? -- Splinter: A Generic Framework for Evolving Modular Finite State Machines -- An Hybrid GA/SVM Approach for Multiclass Classification with Directed Acyclic Graphs -- Dynamic Allocation of Data-Objects in the Web, Using Self-tuning Genetic Algorithms -- Detecting Promising Areas by Evolutionary Clustering Search -- A Fractal Fuzzy Approach to Clustering Tendency Analysis -- On Stopping Criteria for Genetic Algorithms -- A Study of the Reasoning Methods Impact on Genetic Learning and Optimization of Fuzzy Rules -- Using Rough Sets Theory and Minimum Description Length Principle to Improve a ?-TSK Fuzzy Revision Method for CBR Systems -- Robotics and Computer Vision -- Forgetting and Fatigue in Mobile Robot Navigation -- Texture Classification Using the Lempel-Ziv-Welch Algorithm -- A Clustering-Based Possibilistic Method for Image Classification -- An Experiment on Handshape Sign Recognition Using Adaptive Technology: Preliminary Results -- Autonomous Agents and Multi-agent Systems -- Recent Advances on Multi-agent Patrolling -- On the Convergence to and Location of Attractors of Uncertain, Dynamic Games -- Norm Consistency in Electronic Institutions -- Using the oise ?+? for a Cooperative Framework of MAS Reorganisation -- A Paraconsistent Approach for Offer Evaluation in Negotiations -- Sequential Bilateral Negotiation -- Towards to Similarity Identification to Help in the Agents’ Negotiation.

SBIA, the Brazilian Symposium on Arti?cial Intelligence, is a biennial event intended to be the main forum of the AI community in Brazil. The SBIA 2004 was the 17th issue of the series initiated in 1984. Since 1995 SBIA has been accepting papers written and presented only in English, attracting researchers from all over the world. At that time it also started to have an international program committee, keynote invited speakers, and proceedings published in the Lecture Notes in Arti?cial Intelligence (LNAI) series of Springer (SBIA 1995, Vol. 991, SBIA 1996, Vol. 1159, SBIA 1998, Vol. 1515, SBIA 2000, Vol. 1952, SBIA 2002, Vol. 2507). SBIA 2004 was sponsored by the Brazilian Computer Society (SBC). It was held from September 29 to October 1 in the city of S˜ ao Luis, in the northeast of Brazil, together with the Brazilian Symposium on Neural Networks (SBRN). This followed a trend of joining the AI and ANN communities to make the joint event a very exciting one. In particular, in 2004 these two events were also held togetherwiththeIEEEInternationalWorkshoponMachineLearningandSignal Processing (MMLP), formerly NNLP. The organizationalstructure of SBIA 2004was similar to other international scienti?cconferences.Thebackboneofthe conferencewasthe technicalprogram whichwascomplementedbyinvitedtalks,workshops,etc.onthemainAItopics.