Topic

No. of hours

Lecture

Tutorial/Practical

Intelligent Agents.

3

3

-

Solving Problems by Searching.

Informed Search and Exploration.

3

3

-

Constraint Satisfaction Problems.

Adversarial Search.

3

3

-

The Planning Problem, Planning with State-Space Search, Partial-Order Planning.

Planning Graphs, Planning with Propositional Logic, Analysis of Planning Approaches.

3

3

-

Time, Schedules, and Resources, Hierarchical Task Network Planning, Planning and

Acting in Nondeterministic Domains, Continuous Planning, MultiAgent Planning

3

3

-

Learning from Observations.

Forms of Learning, Inductive Learning, Learning Decision Trees, Ensemble Learning.

3

3

-

Natural Language Processing.

A Formal Grammar for a Fragment of English, Syntactic Analysis (Parsing), Efficient parsing .

3

3

-

Augmented Grammars,Semantic Interpretation, Ambiguity and Disambiguation.

Discourse Understanding.

3

3

-

Representing Knowledge in an Uncertain Domain.

3

3

-

The Semantics of Bayesian Networks.

3

3

-

Efficient Representation of Conditional Distribution.

3

3

-

Exact Inference in Bayesian Networks.

3

3

-

Approximate Inference in Bayesian Networks.

3

3

-

Relational and First-Order Probability Models.

3

3

-