Artificial Intelligence syllabus

2019 PATTERN. This is the 2019 pattern syllabus, the latest SPPU has published on its site for Third Year Computer Engineering. A 2024 pattern syllabus for this year has not been published there yet, so confirm with your college which pattern applies to you.

310253 · Third Year Computer Engineering, SPPU 2019 pattern. Every unit, the marks scheme, course outcomes and books, copied from the official syllabus PDF.

3102534 h/week theoryMid-Sem 30 + End-sem 70
06.units
03.credits

Unit-wise syllabus

UNIT I

Introduction

7 hours

Introduction to Artificial Intelligence, Foundations of Artificial Intelligence, History of Artificial Intelligence, State of the Art, Risks and Benefits of AI, Intelligent Agents, Agents and Environments, Good Behavior: Concept of Rationality, Nature of Environments, Structure of Agents.

UNIT II

Problem-solving

7 hours

Solving Problems by Searching, Problem-Solving Agents, Example Problems, Search Algorithms, Uninformed Search Strategies, Informed (Heuristic) Search Strategies, Heuristic Functions, Search in Complex Environments, Local Search and Optimization Problems.

UNIT III

Adversarial Search and Games

7 hours

Game Theory, Optimal Decisions in Games, Heuristic Alpha–Beta Tree Search, Monte Carlo Tree Search, Stochastic Games, Partially Observable Games, Limitations of Game Search Algorithms, Constraint Satisfaction Problems (CSP), Constraint Propagation: Inference in CSPs, Backtracking Search for CSPs.

UNIT IV

Knowledge

7 hours

Logical Agents, Knowledge-Based Agents, The Wumpus World, Logic, Propositional Logic: A Very Simple Logic, Propositional Theorem Proving, Effective Propositional Model Checking, Agents Based on Propositional Logic, First-Order Logic, Representation Revisited, Syntax and Semantics of First-Order Logic, Using First-Order Logic, Knowledge Engineering in First-Order Logic.

UNIT V

Reasoning

7 hours

Inference in First-Order Logic, Propositional vs. First-Order Inference, Unification and First-Order Inference, Forward Chaining, Backward Chaining, Resolution, Knowledge Representation, Ontological Engineering, Categories and Objects, Events, Mental Objects and Modal Logic, Reasoning Systems for Categories, Reasoning with Default Information

UNIT VI

Planning

7 hours

Automated Planning, Classical Planning, Algorithms for Classical Planning, Heuristics for Planning, Hierarchical Planning, Planning and Acting in Nondeterministic Domains, Time, Schedules, and Resources, Analysis of Planning Approaches, Limits of AI, Ethics of AI, Future of AI, AI Components, AI Architectures.

Marks and credits

HeadMarksCredit
Mid-Sem (mid-semester exam)303
End-semester exam70

Prerequisite: Programming and Problem solving (110005), Data Structures and Algorithms (210252).

Course outcomes

  1. CO1Identify and apply suitable Intelligent agents for various AI applications
  2. CO2Build smart system using different informed search / uninformed search or heuristic approaches
  3. CO3Identify knowledge associated and represent it by ontological engineering to plan a strategy to solve given problem
  4. CO4Apply the suitable algorithms to solve AI problems
  5. CO5Implement ideas underlying modern logical inference systems
  6. CO6Represent complex problems with expressive yet carefully constrained language of representation

Books

Text books

Reference books

FAQ

How many units are in Artificial Intelligence?

Artificial Intelligence (310253) has 6 units: Unit I Introduction (7 h); Unit II Problem-solving (7 h); Unit III Adversarial Search and Games (7 h); Unit IV Knowledge (7 h); Unit V Reasoning (7 h); Unit VI Planning (7 h).

What is the marks scheme for Artificial Intelligence?

The official Computer Engineering 2019 pattern syllabus lists mid-semester (Mid-Sem) for 30 marks and the end-semester exam for 70 marks, for 3 credits.

What should I know before Artificial Intelligence?

Prerequisite listed in the syllabus: Programming and Problem solving (110005), Data Structures and Algorithms (210252).