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Showing posts with the label Artificial Intelligence

Artificial Intelligence - R23 - Model Paper 2

  MODEL QUESTION PAPER – 2 (Practice Paper) (B.Tech – III Year I Sem, JNTUK R23 Syllabus) Time: 3 Hours                                                                                                                                             Max. Marks: 70 SECTION – I (10 × 5 = 50 Marks) (Answer ALL questions. Each question has (a) & (b).) Unit – I (Introduction) 1. (a) Discuss the history and foundations of Artificial Intelligence. (5M) (b) Explain problem formulation in AI with example. (5M) (or) 2. (a) Explain characteristics of task environments. (...

Artificial Intelligence - R23 - Important questions.

  Important questions AI - R23 UNIT – I: Introduction Essay (10 Marks) Explain the structure of an intelligent agent with neat diagram and examples. Discuss different types of environments in AI with suitable examples. Explain the foundations and history of Artificial Intelligence. How problem-solving agents work? Illustrate with example. Short Essay (5 Marks) Explain the concept of rationality in AI. Differentiate between agents and environments. Explain the structure of an intelligent agent with a neat sketch. What is problem formulation in AI? Give an example. Explain characteristics of task environments. Write a short note on autonomous agents. Discuss different types of environments with examples. Explain the role of problem-solving agents in AI. Short Answer (2 Marks) Define Artificial Intelligence. Write two real-world applications of AI. What are the foundations of AI? Define intelligent agent. What is an environment in AI? W...

Artificial Intelligence - R23 - Important Topics

UNIT – I: Introduction ✅ Most Important AI problems, foundation of AI, history of AI Intelligent agents: Agents & Environments Structure of agents, problem-solving agents ⭐ Important Concept of rationality, nature of environments ➖ Medium Important Problem formulation UNIT – II: Searching ✅ Most Important Uninformed search strategies: BFS, DFS Heuristic search: Hill climbing, A*, AO* algorithms Game playing: Adversarial search, Mini-max algorithm, Alpha-beta pruning ⭐ Important Problem reduction Optimal decisions in multiplayer games Evaluation functions ➖ Medium Important Problems in Game playing UNIT – III: Representation of Knowledge ✅ Most Important Knowledge representation issues Predicate logic, logic programming Semantic nets, frames & inheritance Rules-based deduction systems ⭐ Important Reasoning under uncertainty Bayes’ probabilistic reasoning ➖ Medium Important Constraint propagatio...

Artificial Intelligence - UNIT 3-Topic 3-Predicate logic and logic programming

  UNIT - III Topic 3 :   Predicate Logic & Logic Programming Part A: Introduction ✅ What is Logic in AI? Logic is the foundation of reasoning in Artificial Intelligence. It allows AI systems to make decisions , derive conclusions , and prove facts using rules and facts . There are two main types of logic used in AI: Propositional Logic Predicate Logic (First-Order Logic) Part B: Predicate Logic (First-Order Logic) ✅ What is Predicate Logic? Predicate Logic , also called First-Order Logic (FOL) , is a powerful logic system that allows the representation of objects, properties, and relationships among objects. It is more expressive than Propositional Logic , which only deals with true or false statements . ✅ Components of Predicate Logic: Component Description Example Predicate Represents a property or relationship Loves(John, Mar...

Artificial Intelligence - UNIT 3-Topic 2-knowledge representation issues

  UNIT - III Topic 2 :   Knowledge Representation Issues Part A: Introduction ✅ What is Knowledge Representation? In AI, Knowledge Representation (KR) refers to the method of encoding information about the world into a format that a computer system can use to solve problems and make decisions . But representing knowledge is not always easy — several issues or challenges arise during this process. These are called Knowledge Representation Issues . Part B: Why are These Issues Important? A poorly designed KR system leads to incorrect or slow decision-making . Understanding these issues helps AI systems to become more reliable , intelligent , and flexible . Part C: Major Issues in Knowledge Representation   1. Representational Adequacy Can the representation capture all kinds of knowledge needed for solving the problem? Some systems cannot represent time, uncertainty, or default values . E...