Private: BE INFORMATION TECHNOLOGY SEM 7 – ARTIFICIAL INTELLIGENCE

Prerequisites
2 Topics
0.1 Prerequisites – Knowledge of any programming language
0.2 Prerequisites – Data structures
Module 1 – Introduction to Intelligent Systems and Intelligent Agents
10 Topics
1.1 Introduction to AI
1.2.a AI Problems and AI techniques
1.2.b AI Problems and AI techniques
1.3 Solving problems by searching
1.4 Problem Formulation
1.5 State Space Representation
1.6 Structure of Intelligent agents
1.7 Types of Agents
1.8 Agent Environments PEAS representation for an Agent
2.1 Uninformed Search – DFS, BFS, Uniform cost search and Iterative Deepening
Module 2 – Search Techniques
11 Topics
2.2.a Informed Search – Heuristic functions
2.2.b Informed Search – Hill Climbing
2.2.c Informed Search – Simulated Annealing
2.2.d Informed Search – Best First Search
2.2.e Informed Search – A*
2.3 Constraint Satisfaction Programming
2.3.a Constraint Satisfaction Programming – Crypto Arithmetic
2.3.b Constraint Satisfaction Programming – Map Coloring
2.3.c Constraint Satisfaction Programming – N-Queens
2.4 Adversarial Search
2.4.a Adversarial Search – Game Playing, Min-Max Search, Alpha Beta Pruning.
Module 3 – Knowledge and Reasoning
6 Topics
3.1 A Knowledge Based Agent
3.2 Overview of Propositional Logic
3.3 First Order Predicate Logic
3.4 Inference in First Order Predicate Logic
3.4.a Inference in First Order Predicate Logic – Forward and Backward Chaining
3.4.b Inference in First Order Predicate Logic –
Module 4 – Planning
5 Topics
4.1 Introduction to Planning
4.2 Planning with State Space Search
4.3 Partial Ordered planning
4.4 Hierarchical Planning
4.5 Conditional Planning
Module 5 – Uncertain Knowledge and Reasoning
5 Topics
5.3 Conditional Probability
5.4 Joint Probability
5.5 Bayes’ theorem
5.1 Uncertainly
5.2 Representing Knowledge in an Uncertain Domain
Module 6 – Natural Language Processing
9 Topics
6.1 Language Models
6.2 Natural Language for Communication
6.2.a Natural Language for Communication – Syntactic Analysis
6.2.b Natural Language for Communication – Augmented Grammars and Semantic Interpretation
6.2.c Natural Language for Communication – Machine Translation
6.3 Overview of Cognitive Computing
6.3.a Overview of Cognitive Computing – Foundation of Cognitive Computing
6.3.b Overview of Cognitive Computing – List of Design Principles for Cognitive Systems
6.3.c Overview of Cognitive Computing – Natural Language Processing in Support of a Cognitive System
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2.4.a Adversarial Search – Game Playing, Min-Max Search, Alpha Beta Pruning.

Private: BE INFORMATION TECHNOLOGY SEM 7 – ARTIFICIAL INTELLIGENCE Module 2 – Search Techniques 2.4.a Adversarial Search – Game Playing, Min-Max Search, Alpha Beta Pruning.
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