
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.
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Problem Solving by Searching- Problem-Solving Agents, Well-defined problems and
solutions, examples Problems, Searching for Solutions, Uninformed Search Strategies-
Breadth-first search, Uniform-cost search, Depth-first search, Depth-limited search,
Iterative deepening depth-first search, Bi directional search
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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.
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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
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Applications of AI- Natural Language Processing, Text Classification and Information
Retrieval, Speech Recognition, Image processing and computer vision, Robotics.Â
- Teacher: Admin User