Artificial Intelligence

Unit 1: Introduction

• Introduction to Artificial Intelligence
• Background and Applications of Artificial Intelligence
• What is Turing test
• Introduction to Weak AI
• Introduction to Strong AI
• Introduction to Narrow AI
• Artificial General Intelligence
• Introduction to Super AI
• Rational agent approaches to AI
• Introduction to Intelligent agents and their structure
• Behaviour and Environment of Intelligent Agents

Unit 2: Problem-Solving and Searching Techniques

• Problem characteristics
• Production systems
• Control strategies
• Breadth-first search
• Depth-first search
• Hill climbing and its variations
• Heuristics search techniques
• Best first search
• A* algorithm
• Constraint satisfaction problem
• means-end analysis
• Introduction to game playing
• min-max and alpha-beta pruning algorithm

Unit 3: Knowledge Representation

• Propositional logic
• first-order predicate logic
• resolution principle
• Introduction to Unification
• Introduction to semantic nets
• conceptual dependencies
• Introduction to frames
• Introduction to scripts
• Production rules
• Introduction to Programming in Logic (PROLOG)

Unit 4: Understanding Natural Language

• Components and steps of communication
• The contrast between formal and natural languages in the context of grammar
• Chomsky Hierarchy of grammars parsing and semantics
• Parsing Techniques
• Context-Free and Transformational Grammar
• Recursive and Augmented transition nets

Unit 5: AI The Present and the Future

• Symbolic AI
• Data-driven AI and Machine Learning
• Bias-Variance tradeoff in Machine Learning
• End-to-end Deep Learning based AI
• Some applications of symbolic and data-driven AI
• Interpretable and Explainable AI
• Ethics of AI: Benefits and risks of AI