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  1. Francesco Ricci; Paolo Avesani,
    Learning an Asymmetric and Anisotropic Similarity Metric for Case-Based Reasoning,
    This paper presents a new class of local similarity metrics, called AASM, that are not symmetric and that can be adopted as basic retrieval method in a CBR system. We also introduce an anytime learning procedure that starting from an initial set of stored cases improves the retrieval accuracy by modifying the local definition of the metric. The learning procedure is an implementation of the reinforcement learning paradigm and can be run as a black box as no particular setting is required. We show with the aid of classical test sets tat AASM cab improve in many cases the accuracy of both nearest Neighbour methods and Salzberg’s NGE. Moreover AASM cab achieve significant data compression (10%) still maintaining the same accuracy of NN,
  2. Paolo Avesani; Anna Perini; Francesco Ricci; M. Rencelj,
    The IP Subsystem - RR50B Charade Restricted Report,
  3. F. Ricci;A. Perini;P. Avesani,
    Building First Intervention Plans: the forest fire case,
    , (the 7-th Workshop on Artificial Intelligence Research in Environmental Science,
    Biloxi, Mississipi,
    11/14/1994, 11/17/1994)
  4. A. Perini;F. Ricci;P. Avesani,
    Temporal reasoning and interactive planning,
    , (Workshop on Temporal Reasoning, AI*IA,
    Parma, Italy,
  5. P. Avesani;A. Perini;F. Ricci,
    Combining CBR and Constraint Reasoning in Planning Forest Fire Fighting,
    , pp. 235-
    , (The First European Workshop on Case-Based Reasoning (EWCBR '93),
    Kaiserslautern, Germany,
  6. Francesco Ricci; Anna Perini; Paolo Avesani,
    Planning in a Complex Real Domain,
    Dimensions of complexitiy raised during the definition of a system aimed at supporting the planning of initial attack to forest fires are presented and discussed. The complexity deriving from the highly dynamic and unpredictable domain of forest fire, the one related to the individuation and integration of planning techniques suitable to this domain, the complexity of addressing the problem of taking into account the role of the user to be supported by the system and finally the complexity of an architecture able to integrate different subsystems. In particular we focus on the severe constraints to the definition of a planning approach posed by the fire fighting domain, constraints which cannot be satisfied completely by any of the current planning paradigms. We propose an approach based on the integration of skeletal planning and case based reasoning techniques with constraint reasoning. More specifically temporal constraints are used in two steps of the planning process: plan fitting and adaptation, and resource scheduling. Work on the development of the system software architecture with a OOD methodology is in progress,
  7. Paolo Avesani,
    Integrazione CAD-CAM: utilizzo di sistemi esperti nella pianificazione di processo,
    Second International Conference: The Use of Expert Systems in the Automative and Aerospace Industries,
  8. Paolo Avesani; Anna Perini; Francesco Ricci,
    COOL: an Object System with Constraints,
    Bezivin J., Meyer B., Nerson J. (eds.), Technology of Object-Oriented Languages and Systems, Proceedings of the Second International Conference TOOLS90,
    , pp. 221-