Course Program
Artificial Intelligence (6CFU)
Introduction to Artificial Intelligence
Knowledge Representation
Representing models of the domain of interest
Enabling autonomy
The role of logic
Propositional Logic
Propositional formulas, and knowledge-bases
Evaluation (Model Checking), Satisfiability, Validity, Logical Implication
Tableaux
DPLL, SAT solvers
First-Order Logic
Evaluation in First-Order Logic
Reasoning in First-Order Logic
Tableaux
UML Class Diagrams as Knowledge Bases
Incomplete information and Conjunctive Queries
Reasoning about Actions
Modeling dynamics of the domain of interest
Deliberating and executing actions
Action Preconditions, Effects, the Frame Problem,
Situation Calculus: Precondition Axioms, Successor State Axioms
Situation tree
Regression
Executability of sequences of actions and Projection (querying a situation resulting from action sequences execution)
Planning in Deterministic Domains
Deterministic Planning Domains
STRIPS, ADL, Planning Domain Description Language (PDDL)
Transition Systems
Planning by backward fixpoint computations
Planning by forward search, Heuristics, Best-first, A*
Planning in Nondeterministic Domains (FOND)
Nondeterministic Planning Domains
PDDL with oneof operator
Game Theoretic View
Nondeterministic Planning by backward fixpoint computations
Nondeterministic Planning by Adversarial Search, Search in AND-OR Graphs
Machine Learning
Introduction to Machine Learning
Basics on Probability (Review)
Supervised Learning:
Linear Classification
Linear Regression
Neural Networks
Unsupervised Learning
Reinforcement Learning