Artificial and Computational Intelligence
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Artificial and Computational Intelligence Syllabus — Unit-wise Content
The official GTU curriculum for Artificial and Computational Intelligence (subject code 1719501) as prescribed for AIAD · Semester 1 divides the course into 6 units, covering 55 listed topics. The unit-wise breakdown below is read from the GTU syllabus document for this subject code, so you can check what the course actually covers before deciding which papers to attempt.
Download the official syllabus PDF (1719501)Unit 1 Intelligent Agents and Problem Solving
- What is AI, Foundation of AI, The State of the Art, Agents and Environments
- Good Behavior: The Concept of Rationality
- The Nature of Environments
- The Structure of Agents
- Problem Solving Agents
- Example Problems
- Uninformed Search Strategies
- Informed (Heuristic) Search Strategies
- Heuristic Functions
- Optimal Decisions in Games
- Alpha-Beta Pruning
- Stochastic Games
- Partially Observable Games
- State-of-the-Art Game Programs
- Constraint Satisfaction Problems (CSP)
- Inference in CSPs
- Backtracking Search in CSPs
- Local Search for CSPs BRANCH: COMPUTER ENGINEERING (ARTIFICIAL INTELLIGECNE AND DATA SCIENCE) Page 2
Unit 2 Knowledge, Reasoning and Planning
- Propositional Logic
- First-Order Logic
- Knowledge Engineering in First-Order Logic
- Propositional vs
- First Order Inference
- Forward Chaining
- Backward Chaining
- Classical Planning
- Planning Graphs
- Hierarchical Planning
- Multiagent Planning
Unit 3 Uncertain Knowledge and Reasoning
- Basic Probability Notion
- Inference using Full Joint Distributions
- Bayes’ Rule and its Use, Representing Knowledge in an Uncertain Domain
- The Semantics of Bayesian Networks
- Exact Inference in Bayesian Networks
- Approximate Inference in Bayesian Networks
- Relational and First-Order Probability Models
Unit 4 Learning, Communicating, Perceiving and Acting
- Supervised Learning
- Evaluating and Choosing the Best Hypothesis
- Knowledge in Learning
- Explanation-based Learning
- Language Models
- Text Classification
- Information Retrieval
- Information Extraction
- Robot Hardware
- Robotic Perception
- Planning to Move
- Planning Uncertain Movements
- Robotics Software Architectures
Unit 5 Ethics for Artificial Intelligence
- Five Areas of Ethical Focus: Accountability
- Value Alignment
- User Data Rights
Unit 6 Recent Trends in the Domain of Artificial and Computational Intelligence 4 10% Textbook
- Artificial Intelligence – A Modern Approach by Stuart Russel and Peter Norvig Third Edition
- Prentice Hall Series. 2
- Everyday Ethics for Artificial Intelligence IBM Corporation
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