General question : What is 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
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
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
Discussion of embodied intelligence and autonomous agents
Roboter programming :
Braitenberg's vehicles and Brooks' subsumption architecture
Foundations and applications of multi-agent systems
Students should also be able to plan and realize projects based on the presented concepts.
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