Lecture presentations (in Slovak)

Introduction (symbolic AI, rational agent and environment)
(pdf
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Search space
(pdf
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Uninformed state space search (breadth/depth first, iter.deepening, uniform cost)
(pdf
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Informed state space search (greedy search, A*)
(pdf
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Search in different environments (memory bounded)
(pdf
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Game tree search (minimax, alfabeta prunning, expectimax)
(pdf verzia)


Constraints (consistency enforcing, search)
(pdf
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DPLL algorithm
(pdf
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Prolog and Clips


Propositional and firstorder logics (syntax, semantics,
inference)
(pdf
verzia)

Internet demos
Code experiments
Software online tools

Code snippets

Students' projects (2018)
Auxiliary code for Mancala project

Sudoku

Topics
 Definition of symbolic artificial intelligence
 Rational agent
 Environment types
 State space definition
 Search tree (tree nodes versus states)
 Properties of search strategies
 Breadthfirst search  algorithm, properties
 Depthfirst search  algorithm, properties, depth limitation
 Iterative deepening, bidirectional search
 Bestfirst search  algorithm structure
 Cost function types (uniformcost search, greedy search, A* search)
 A*  heuristic function admissibility deduction
 Optimality and complexity of A*
 A*  comparison of heuristics
 Creation of heuristics
 Propositional logic (syntax, semantics)
 Knowledge representation (grounding, variables, constraints)
 CNF (syntax, transformation)
 Inference in propositional logic (model searching, deduction)
 Resolution in propositional logic (principles)
 DPLL algorithm (basic form, extensions)
 Implication graph, conflict analysis
 Zero/First order predicate logic (syntax)
 Variables in FOL (free/close variables, quantifiers)
 Semantics of FOL (interpretations)
 Knowledge representation in FOL, transformation to CNF
 Inference in FOL (model checking, direct proof, proof by refutation)
 Resolution in first order logic
 Unification of literals
 Resolutionbased algorithm (extensions)
 Answering questions in FOL
 Derivation graph, resolution strategies
 Semantic networks (structure,elements)
 Inference in semantic networks
 Frames and scripts (slots, facets, ifneeded, ifadded, ifdeleted)
 Constraints (domains, explicit and induced constraints, search space)
 Consistency ((i,j)consistency, arc, path and inverse path consistency)
 Consistency enforcing algorithms (AC)
 Combination of consistency levels (RPC, kRPC, maxRPC)
 Searchbased solving of constrained problems (backtracking)
 Search improvement  jump algorithms (conflictdirected backjumping)
 Search improvement  memory algorithms (backchecking, nogoods recording)
 Search improvement  ordering algorithms (variable ordering, value ordering)
 Combination of consistency and search algorithms (forward checking)
 Horn logic
 Forward chaining (principle, resolution rule, hyperresolution)
 Forward chaining algorithm
 Production system (basic concepts, Clips)
 Production cycle (agenda, activations, rule firing)
 Rete network structure (alpha and beta networks, node types)
 Propagation of working memory changes through Rete network
 Negation in Rete network (single and double negation)
 Backward chaining (principle, resolution rule)
 Backward chaining algorithm
 Prolog (syntax, depthfirst database searching)
 Box model
