BCA VI Sem AI Resources 2026

🔹 Unit I: Introduction

• What is Artificial Intelligence
• Foundations of AI
• History of AI – Past, Present and Future

Intelligent Agents

• Environments
• Specifying the task environment
• Properties of task environments

Agent-Based Programs

• Structure of agents
• Types of agents:
  • Simple reflex agents
  • Model-based reflex agents
  • Goal-based agents
  • Utility-based agents

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🔹 Unit II: Problem Solving by Searching

• Problem-solving agents
• Well-defined problems and solutions
• Example problems
• Searching for solutions

Uninformed Search Strategies

• Breadth-first search
• Uniform-cost search
• Depth-first search
• Depth-limited search
• Iterative deepening depth-first search
• Bidirectional search

Informed (Heuristic) Search Strategies

• Greedy best-first search
• A* search
• AO* search
• Heuristic search steps
• Heuristic functions

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🔹 Unit III: Knowledge Representation

Knowledge-Based Agents

• Knowledge-based agent concepts

Propositional Logic

• Propositional logic
• Propositional theorem proving
• Effective propositional model checking
• Agents based on propositional logic

First-Order Logic

• Syntax and semantics of first-order logic
• Using first-order logic

Inference in First-Order Logic

• Unification and lifting
• Forward chaining
• Backward chaining

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🔹 Unit IV: Learning and Applications

Learning

• Forms of learning
• Supervised learning

Machine Learning Techniques

• Decision trees
• Regression and classification using linear models
• Artificial Neural Networks
• Support Vector Machines

Applications of AI

• Natural Language Processing
• Text classification and information retrieval
• Speech recognition
• Image processing and computer vision
• Robotics

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📖 References

• Elaine Rich, Kevin Knight, Shivashankar B. Nair – Artificial Intelligence, Tata McGraw Hill, 2013
• Stuart Russell, Peter Norvig – Artificial Intelligence: A Modern Approach, Pearson
• Tom Mitchell – Machine Learning, McGraw-Hill, 2017