Artificial Intelligence

 Course Objectives :                          Why this Subject? | AI Glossary

1. To impart the definition and basic knowledge of Artificial Intelligence.
2. To introduces AI by examining the nature of the difficult problems.
3. To understand with AI demonstration that intelligence requires ability to find reason.
4. To understand the latest techniques and the future scope of the technology.

Course Outcomes (CO)

• CO1 Ability to use AI methods and control strategies to solve the problems.
• CO2 Understand the production system and its applications. Also, to understand the properties and applications for the different search algorithms.
• CO3 Applying the different algorithms and the techniques, also analyse the reason for the results.
• CO4 Study the expert systems and the modern approaches.

UNIT-I

AI Definition, Problems, The Foundations of Artificial Intelligence, Techniques, Models, Defining Problem as a state space search, production system, Intelligent Agents: Agents and Environments, Characteristics, Search methods and issues in the design of search problems.

UNIT-II

Knowledge representation issues, mapping, frame problem. Predicate logic, facts in logic, representing instance and Isa relationship, Resolution, procedural and declarative knowledge, matching, control knowledge. Symbolic reasoning under uncertainty, Non monotonic reasoning, statistical reasoning.

UNIT-III

Game Playing, minimax search, Alfa beta cut-offs, Natural Language Processing, Learning, Explanation-based learning, discovery, analogy, Neural net learning and Genetic Learning.

UNIT - IV

Fuzzy logic systems, Perception and action, Expert systems, Inference in Bayesian Networks, K-means Clustering Algorithm, Machine learning.

Textbook(s):

1. Elaine Rich, Kevin Knight, and Shivashankar B Nair, “Artificial Intelligence”, Tata McGraw Hill.
2. S. Russel and P. Norvig, “Artificial Intelligence: A Modern Approach”, Pearson Edu.

References:

1. Deepak Khemani, “A First Choice in Artificial Intelligence”, McGraw Hill.
2. K M Fu, “Neural Networks in Computer Intelligence”, McGraw Hill.