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Subject Syllabus

AL-304 - Artificial Intelligence

AIML • SEMESTER-3

Course Modules

Learn topic-wise with Hyper AI and revise using mapped PYQs.

Fundamental of Artificial IntelligenceHistory, motivation and need of AIProduction systemsCharacteristics of production systemsGoals and contribution of AI to modern technologySearch spaceDifferent search techniques: hill Climbing, Best first Search, heuristic search algorithm, A* and AO* search techniques etc.
Knowledge RepresentationProblems in representing knowledgeKnowledge representation using propositional and predicate logicComparison of propositional and predicate logicResolution, refutation, deduction, theorem provingInferencingMonotonic and non-monotonic reasoning
Probabilistic reasoningBaye's theoremSemantic networks, scripts, schemas, framesConceptual dependencyForward and backward reasoning
Game playing techniques like minimax procedure, alpha-beta cut-offs etcPlanningStudy of the block world problem in roboticsIntroduction to understandingNatural language processing (NLP)Components of NLPApplication of NLP to design expert systems
Expert systems (ES) and its CharacteristicsRequirements of ESComponents and capability of expert systemsInference Engine Forward & backward ChainingExpert Systems LimitationExpert System Development Environment, technologyBenefits of Expert Systems