JNTUK R19 B.Tech CSE 3-1 Artificial Intelligence Material/ Notes PDF Download

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JNTUK R19 B.Tech CSE 3-1 Artificial Intelligence Material/ Notes PDF Download: Looking for a study for your JNTUK R19 B.Tech CSE 3-1 Artificial Intelligence Material. Our content covers all you need! Get notes, lectures, and PDF downloads to help you understand AI concepts easily. From basic proficiency in traditional AI languages to advanced topics like natural language processing and robotics, we’ve got it all. With our material, you’ll learn about coding, knowledge representation, and search techniques step by step. It’s the perfect resource to excel in your AI studies and exams. Download now and start mastering AI.

JNTUK R19 B.Tech CSE 3-1 Artificial Intelligence Material – Units

Unit 1 Syllabus PDF Download | JNTUK R19 B.Tech CSE Artificial Intelligence Material

Introduction: History, intelligent systems, foundations of AI, applications, tic-tac-toe game playing, development of AI languages, current trends.

Unit 2 Syllabus PDF Download | JNTUK R19 B.Tech CSE Artificial Intelligence Material

Problem-solving: state-space search and control strategies: Introduction, general problem solving, characteristics of the problem, exhaustive searches, heuristic search techniques, iterative deepening A*, constraint satisfaction.

Problem reduction and game playing: Introduction, problem reduction, game playing, alpha beta pruning, two-player perfect information games.

Unit 3 Syllabus PDF Download | JNTUK R19 B.Tech CSE Artificial Intelligence Material

Logic concepts: Introduction, propositional calculus, proportional logic, natural deduction system, axiomatic system, semantic tableau system in proportional logic, resolution refutation in proportional logic, predicate logic.

Unit 4 Syllabus PDF Download | JNTUK R19 B.Tech CSE Artificial Intelligence Material

Knowledge representation: Introduction, approaches to knowledge representation, knowledge representation using semantic network, extended semantic networks for KR, knowledge representation using frames. Advanced knowledge representation techniques: Introduction, conceptual dependency theory, script structure, CYC theory, case grammars, semantic web

Unit 5 Syllabus PDF Download | JNTUK R19 B.Tech CSE Artificial Intelligence Material

Expert system and applications: Introduction phases in building expert systems, expert system versus traditional systems

Uncertainty measure: probability theory: Introduction, probability theory, Bayesian belief networks, certainty factor theory, dempster-shafer theory Fuzzy sets and fuzzy logic: Introduction, fuzzy sets, fuzzy set operations, types of membership functions, multi-valued logic, fuzzy logic, linguistic variables and hedges, fuzzy propositions, inference rules for fuzzy propositions, fuzzy systems.

JNTUK R19 B.Tech Artificial Intelligence Material – Outcomes

• Recognize problems suitable for AI methods such as image classification or route planning.
• Choose appropriate AI techniques based on the problem’s characteristics.
• Develop tailored AI algorithms, using standard search or dynamic programming as needed.
• Conduct experiments to compare algorithm performance on various inputs.
• Analyze empirical results to conclude algorithm effectiveness for informed decision-making.

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