| 11-October-2021 |
1.5 hours |
Introduction to Artificial Intelligence. |
Q&A session |
|
|
1.5 hours |
Foundations and history of AI |
Q&A session |
|
| 18-October-2021 |
1.5 hours |
Types of AI, Basic components of AI |
Elaborate, Intelligence activities |
|
|
1.5 hours |
Artificial agents, types of agents |
Classify, act of agent on bases of the percept |
|
| 25-October-2021 |
1.5 hours |
Agent’s environment, types of environments. |
Identify the agent type and environment |
|
|
1.5 hours |
State space graphs and search trees, solving problems by searching, problem solving agents. |
Visualize your problem by Graph |
|
| 1-November-2021 |
1.5 hours |
Uniformed search: Breadth -First search with examples. |
Identify the class of searching problem |
|
|
1.5 hours |
Uniformed search: Depth -First search with examples. |
Quiz #1 |
|
| 8-November-2021 |
1.5 hours |
Uniformed search: Uniform Cost with examples. |
Differentiate Searching algorithms |
|
|
1.5 hours |
Informed Search: Greedy search. |
Example of TSP |
|
| 15-November-2021 |
1.5 hours |
Informed Search: A* search. |
Example of TSP |
|
|
1.5 hours |
Beyond classical search: Hill-climbing search, random restart hill climb search |
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|
| 22-November-2021 |
1.5 hours |
Beyond classical search: Simulated annealing |
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|
|
1.5 hours |
Revision |
|
|
| 29-November-2021 |
1 Hour |
Mid Term |
|
|
| 6-December-2021 |
1.5 hours |
Beyond classical search: local beam search |
|
|
|
1.5 hours |
Beyond classical search: Genetic algorithms |
|
|
| 13-December-2021 |
1.5 hours |
Mid Term |
|
|
|
1.5 hours |
Mid Term |
|
|
| 20-December-2021 |
1.5 hours |
Adversarial Search: Minimax algorithm |
|
|
|
1.5 hours |
Adversarial Search: Efficiency of Minimax Algorithm, Optimal decisions in games |
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|
| 27-December-2021 |
1.5 hours |
Adversarial Search: alpha-beta pruning |
|
|
|
1.5 hours |
Constraint satisfaction problem: Part I |
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|
| 3-January-2022 |
1.5 hours |
Constraint satisfaction problem: Part II |
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|
|
1.5 hours |
Logical agents: Knowledge-based agents |
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| 10-January-2022 |
1.5 hours |
Logical agents: Propositional logic |
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|
|
1.5 hours |
Logical agents: Forward chaining |
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|
| 17-January-2022 |
1.5 hours |
Logical agents: Backward chaining |
|
|
|
1.5 hours |
First-order logic: representation revisited, Knowledge engineering in first-order logic |
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|
| 24-January-2022 |
1.5 hours |
Learning: Regression and Classification |
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|
|
1.5 hours |
Learning from examples: Artificial Neural Networks |
|
|
| 31-January-2022 |
2 Hour |
Final Term |
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