Artificial Intelligence I
Definition, history, relations with other scientific fields. Intelligent agents: rationality, performance metrics, work environments, structure of agents. Problem solving with search: State spaces, search trees, uninformed search methods (depth-first, breadth-first), search with partial information. Informed search and exploration: Best First and A* algorithms, local search algorithms (Hill climbing, simulated annealing, genetic algorithms). Constraint satisfaction problems: Constraint propagation, early check, arc consistency. Adversarial search: Optimal strategies in two-person games, minimax algorithm, alpha-beta pruning, extension to multiplayer games, extension to games of chance, expectiminimax algorithm. Logical agents: Propositional logic, inference patterns, resolution, logic circuits, first-order logic, inference rules for quantifiers, unification, inference chains, theorem proving, logic programming, introduction to Prolog language. Knowledge representation: Ontologies, representation of categories, objects, actions, states and occurences, semantic networks, description logics.
Artificial Intelligence II
Search based planning, logic based planning, planning graphs, resource-constrained time scheduling, hierarchical task networks, planning in non-deterministic fields, multi-agent planning. Action under uncertainty: Bayes networks, probabilistic reasoning, approximate reasoning, reasoning with Markov chains, fuzzy logic, temporal model reasoning, hidden Markov models, Kalman filters, dynamic Bayes networks, applications in speech recognition. Decision making: Utility theory, multimodal utility functions, decision networks, expert systems, game theory. Machine learning: Decision trees, inductive learning, explanation based learning, inductive logic programming, statistical learning methods, naive Bayes models, EM algorithm, Gauss learning, instance learning, kernel models and machines, neural networks, reinforcement learning. Communication: Formal grammars and languages, syntactic analysis, semantic interpretation, DCG grammars, ambiguity resolution, text understanding, stochastic language models, PCFG grammars, information extraction, machine translation. Perception and action: Machine vision, object identification from images, robotic perception, location and mapping, robotic sensors and actuators, movement planning, robotic software architectures.
Computational Geometry & 3D Modeling
Graphics & Virtual Reality