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 note explains the following topics: State Space
Search, Decision Trees, Evaluating Hypotheses, Evaluation of hypothesis, Neural
Networks, Computational Learning Theory, DMF Clustering, Data Mining, Text
Mining, Graph Mining, Text Mining.
This note provides an introduction to artificial intelligence.
Topics covered include: representation and inference in first-order logic,
modern deterministic and decision-theoretic planning techniques, basic
supervised learning methods, and Bayesian network inference and learning.
Author(s): Prof. Tomas Lozano-Perez and Prof.
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
book is for both professional programmers and home hobbyists who already
know how to program in Java and who want to learn practical Artificial
Intelligence (AI) programming and information processing techniques. Topics
covered includes: Search, Reasoning, Semantic Web, Expert Systems, Genetic
Algorithms, Neural Networks, Machine Learning with Weka, Statistical Natural