Anna University Artificial Intelligence Notes
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Syllabus :
CS2351 ARTIFICIAL INTELLIGENCE L T P C
UNIT I PROBLEM SOLVING 9
Introduction – Agents – Problem formulation – uninformed search strategies – heuristics– informed search strategies – constraint satisfaction
UNIT II LOGICAL REASONING 9
Logical agents – propositional logic – inferences – first-order logic – inferences in firstorder logic – forward chaining – backward chaining – unification – resolution
UNIT III PLANNING 9
Planning with state-space search – partial-order planning – planning graphs – planning and acting in the real world
UNIT IV UNCERTAIN KNOWLEDGE AND REASONING 9
Uncertainty – review of probability - probabilistic Reasoning – Bayesian networks –inferences in Bayesian networks – Temporal models – Hidden Markov models
UNIT V LEARNING 9
Learning from observation - Inductive learning – Decision trees – Explanation based learning – Statistical Learning methods - Reinforcement Learning
You Can Download The Material Of Artificial Intelligence From The Below Link
Syllabus :
CS2351 ARTIFICIAL INTELLIGENCE L T P C
UNIT I PROBLEM SOLVING 9
Introduction – Agents – Problem formulation – uninformed search strategies – heuristics– informed search strategies – constraint satisfaction
UNIT II LOGICAL REASONING 9
Logical agents – propositional logic – inferences – first-order logic – inferences in firstorder logic – forward chaining – backward chaining – unification – resolution
UNIT III PLANNING 9
Planning with state-space search – partial-order planning – planning graphs – planning and acting in the real world
UNIT IV UNCERTAIN KNOWLEDGE AND REASONING 9
Uncertainty – review of probability - probabilistic Reasoning – Bayesian networks –inferences in Bayesian networks – Temporal models – Hidden Markov models
UNIT V LEARNING 9
Learning from observation - Inductive learning – Decision trees – Explanation based learning – Statistical Learning methods - Reinforcement Learning
You Can Download The Material Of Artificial Intelligence From The Below Link
