Introduction- What is Artificial Intelligence, Foundations of AI, 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; and Utility-based agents.
Problem Solving by Searching- Problem-Solving Agents, Well-defined problems and
solutions, examples Problems, Searching for Solutions, Uninformed Search StrategiesBreadth-first search, Uniform-cost search, Depth-first search, Depth-limited search, Iterative deepening depth-first search, Bi directional search
Knowledge Representation- Knowledge-Based Agents, The Wumpus World, 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, Unification and Lifting Forward Chaining,
Backward Chaining.
Learning– Forms of Learning, Supervised Learning- Artificial Neural Networks (ANN), Support Vector Machines (SVM), Unsupervised Learning: Clustering, Association.
Advantages and disadvantages of Unsupervised Learning, Hill Climbing Algorithm
Applications of AI- Natural Language Processing, Text Classification and Information Retrieval, Speech Recognition, Image processing and computer vision, Robotics.
- Teacher: Admin User