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Cours: Intelligence artificielle
The main objective of this course is to introduce the students to the various strategies that can be used to help computers
Practical exercises will complete the theoretical presentation.
Intelligent agent paradigm; Uninformed search (depth-first search, breadth-first search); Informed search (A*, heuristics); Local search (hill climbing, simulated annealing) ; Genetic programming ; Constraint satisfaction problem, AND/OR tree; Games (minimax, alpha-beta algorithm) ; Knowledge representation (proposition, predicates, frames, semantic nets, rules) ; Expert-system (forward and backward chaining) ; Neural networks ; Machine learning (Naive Bayes); Planning.
The final mark is based on both a final written exam and the results of the practical exercices.
To get a version of Prolog