Artificial Intelligence (Syllabus + Books) [2018-2019]

Artificial Intelligence (Syllabus) [2018-2019]

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Course: Artificial Intelligence
Unit – I
Introduction:

• What is Artificial Intelligence?
• Foundations of AI
• History
• The State Of Art AI Today

Intelligent Agents:

• Agents And Environment
• Good Behavior
• Nature Of Environment
• The Structure Of Agents

Unit – II
Solving Problems By Searching:

• Problem Solving Agents
• Examples Problems
• Searching For Solutions
• Uninformed Search
• Informed Search Strategies
• Heuristic Functions

Beyond Classical Search:

• Local Search Algorithms
• Searching With Non-Deterministic Action
• Searching With Partial Observations
• Online Search Agents And Unknown Environments

Unit – III
Adversarial Search:

• Games
• Optimal Decisions In Games
• Alpha-Beta Pruning
• Stochastic Games
• Partially Observable Games
• State-Of-The-Are Game Programs

Logical Agents:

• Knowledge Base Agents
• The Wumpus World
• Logic
• Propositional Logic
• Propositional Theorem Proving
• Effective Propositional Model Checking
• Agents Based On Propositional Logic

Unit – IV
First Order Logic:

• Syntax And Semantics
• Using First Order Logic
• Knowledge Engineering In First Order Logic

Inference In First Order Logic:

• Propositional vs. First Order
• Unification And Lifting
• Forward And Backward Chaining
• Resolution

Unit – V
Planning:

• Definition Of Classical Planning
• Algorithms For Planning As State Space Search
• Planning Graphs
• Other Classical Planning Approaches
• Analysis Of Planning Approaches
• Time
• Schedules And Resources
• Hierarchical Planning
• Planning And Acting In Nondeterministic Domains
• Multiagent Planning

Knowledge Representation:

• Categories And Objects
• Events
• Mental Events And Objects
• Reasoning Systems For Categories
• Reasoning With Default Information
• Internet Shopping World