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Undergraduate

Artificial Intelligence

Compulsory course for Third Year students of the Faculty of Computer Systems. Offered in Fall.

Instructor: Adrian Groza

Course content

The state of the art

Turing test, acting humanly, thinking humanly, acting rationally, applications, explainable AI

Intelligent agents

agents and environments, rational agents, structure of agents

Solving problems by searching

uninformed search, informed search, A* search, heuristic functions

Beyond classical search

local search, hill climbing, simulated annealing, local beam search, genetic algorithms, searching with non-deterministic actions, searching with partial observation

Adversarial search

games, and-or search trees, min-max, alpha-beta pruning, imperfect-real time decisions, stochastic games, partially observable games, state of the art game programs

Constraint satisfaction problems(CSPs)

defining CSP problems, constraint propagation, node consistency, arc consistency, path consistency, local search for CSPs, heuristics for CSPs

Logical agents

knowledge-based agents, propositional logic (PL), theorem proving, reasoning in PL, satisfiability, Davis-Putnam algorithm, modelling in PL, solving logical puzzles in PL

First order logic (FOL)

syntax and semantics of FOL, knowledge engineering in FOL, solving logical puzzles in FOL

Inference in FOL

unification and lifting, forward and backward chaining, resolution in FOL, theorem proving, finite models finding in FOL

Classical planning

planning as a state-space search, planning graphs, partial planning, planning domain definition language, planning in situation calculus, heuristics for planning; solving planning puzzles

Planning and acting in the real-world

time, schedules, resources, minimum slack algorithm, hierarchical planning, conformant planning, contingent planning, multi-agent planning

Knowledge representation

event calculus (EC), commonsense reasoning, prediction, abduction and postdiction in EC, modelling patterns in EC, event monitoring, reasoning about commitments in EC

Multi-agent systems

Beliefs, desires, intentions, AgentSpeak programming language, Jason, goals, events, alternative plans, cooperation and coordination, concurrent actions

Main bibliography

  1. Russell, Stuart J., and Peter Norvig. Artificial intelligence: a modern approach. 4th edition, 2020
  2. A. Groza, R.R. Slavescu, A. Marginean. Introduction to Artificial Intelligence, U.T. Press, 2018

Additional bibliography

  1. van Benthem J, van Ditmarsch H, van Eijck J, Jaspars J. Logic in Action, 2016
  2. Ghallab, Malik, Dana Nau, and Paolo Traverso. Automated planning and acting. Cambridge University Press, 2016
  3. Mueller, Erik T. Commonsense reasoning: an event calculus based approach. Morgan Kaufmann, 2014
  4. Bordini, Rafael H., Jomi Fred Hübner, and Michael Wooldridge. Programming multi-agent systems in AgentSpeak using Jason. Wiley, 2007
  5. Millington, Ian, and John Funge. Artificial intelligence for games. 3rd edition, CRC Press, 2019
  6. Rossi, Francesca, Peter Van Beek, and Toby Walsh, eds. Handbook of constraint programming. Elsevier, 2006