Advanced Topics in Artificial Intelligence

AI: Introduction, paradigms, applications (including CBR), impacts, visions.- Artificial intelligence and connectionism: Some philosophical implications.- Logic for representing and implementing knowledge about system behaviour.- Prolog: A step towards the future of programming.- An introduction to constraint logic programming.- Logic and databases.- to machine learning.- Approaches to inductive logic programming.- Advanced machine learning techniques for computer vision.- Notes on current trends in AI planning.- The application of reason maintenance systems in planning and scheduling.- Practical applications of planning tasks.- The role of uncertainty measures and principles in AI.- to probabilistic methods of knowledge representation and processing.- On belief functions.- Data analysis and uncertainty processing.- Some aspects of knowledge engineering.- An automatic knowledge acquisition tool.- Distributed AI and its applications.- Architectures for second generation knowledge based systems.- An introduction to qualitative reasoning.- Model-based diagnosis: An overview.- Dynamic system simulation with qualitative differential equations.- An introduction to neurocomputing and its possible role in AI.- Intelligent presentation and dialogue management.- Linguistic aspects of natural language processing.