explains the following topics: Principles of knowledge-based search techniques,
automatic deduction, knowledge representation using predicate logic, machine
learning, probabilistic reasoning, Applications in tasks such as problem
solving, data mining, game playing, natural language understanding, computer
vision, speech recognition, and robotics.
This lecture note
covers the following topics: Introduction to Agent, Problem Solving using
Search, State Space Search, Pegs and Disks problem, Uninformed Search , Single
agent search, Informed Search Strategies, Two agent, Constraint satisfaction
problems, Knowledge Representation and Logic, First Order Logic, Rule based
Systems, Other representation formalisms, Planning, Reasoning with Uncertainty -
Probabilistic reasoning, Reasoning with uncertainty-Fuzzy Reasoning.
This book explains the following
topics: Scope of Artificial Intelligence, Problem Solving, Knowledge
Representation, Rule Based Systems, Structured Knowledge Representation,
Handling Uncertainty and Learning, Expert Systems.
Author(s): Guru Jambheshwar
University of Science and Technology, Hisar
AI is the part of computer science concerned with designing intelligent
computer systems, that is, computer systems that exhibit the characteristics we
associate with intelligence in human behaviour - understanding language,
learning, reasoning and solving problems .A theme we will develop in this course
note is that most AI systems can broken into: Search, Knowledge Representation
and applications of the above.