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Intelligent SystemsGeneral question : What is intelligence ? Connectionistic Intelligence Introduction : From single neurons to brain structures Learning in biological systems Modelling of artificial neurons and artificial neural networks General features and training of such networks Realisations : Neural gates, perceptrons, linear associators, recurrent networks, and self organizing feature maps Current trends : Spiking neural networks Adaptive Intelligence Introduction : Genes and evolution Basics : Variation and selection Realisation and applications of genetic algorithms Theoretical foundations : Schemata and building blocks Current trends : Population structures, migration and diffusion models Cognitive Intelligence Introduction : Cognitve psychology and the symbol system hypotheses Logic systems : from assertations to predicates Reasoning with STRIPS Concepts : Production systems, search in state spaces, and heuristics Representations : Frames, scripts, and semantic networks Realisation : Expert systems Situated Intelligence Discussion of embodied intelligence and autonomous agents Roboter programming : Braitenberg's vehicles and Brooks' subsumption architecture Emergent Intelligence Foundations and applications of multi-agent systems Students should also be able to plan and realize projects based on the presented concepts. Detaillierte Informationen durch ein Mail an den Referenten . |