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Description 1
This course enables learning on different graph traversal techniques (BFS & DFS)
along with enhanced search algorithms like A* algorithm. Genetic algorithms are discussed along with Min-Max algorithms.
Expert systems and ANN are also discussed in detail along with Fuzzy logic in SC.
Along with a pdf with important notes and explanations
Modules Covered:
Introduction to AI / SC
Problem solving algorithms
Knowledge, Reasoning and Planning.
Fuzzy Logic.
Artificial Neural Network.
Expert System.-
Lecture1.1
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How to Pass AISC 1
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Lecture2.1
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Introduction to Artificial Intelligence(AI) and Soft Computing 5
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Lecture3.1
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Lecture3.2
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Lecture3.3
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Lecture3.4
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Lecture3.5
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Problem Solving 10
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Lecture4.1
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Lecture4.2
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Lecture4.3
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Lecture4.4
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Lecture4.5
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Lecture4.6
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Lecture4.7
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Lecture4.8
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Lecture4.9
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Lecture4.10
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Fuzzy Logic 6
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Lecture5.1
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Lecture5.2
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Lecture5.3
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Lecture5.4
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Lecture5.5
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Lecture5.6
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Knowledge, Reasoning and Planning 6
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Lecture6.1
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Lecture6.2
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Lecture6.3
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Lecture6.4
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Lecture6.5
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Lecture6.6
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Artificial Neural Network 7
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Lecture7.1
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Lecture7.2
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Lecture7.3
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Lecture7.4
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Lecture7.5
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Lecture7.6
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Lecture7.7
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Expert System 4
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Lecture8.1
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Lecture8.2
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Lecture8.3
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Lecture8.4
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Notes 6
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Lecture9.1
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Lecture9.2
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Lecture9.3
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Lecture9.4
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Lecture9.5
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Lecture9.6
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Extra Notes 9
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Lecture10.1
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Lecture10.2
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Lecture10.3
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Lecture10.4
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Lecture10.5
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Lecture10.6
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Lecture10.7
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Lecture10.8
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Lecture10.9
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Introduction to Hybrid System
Introduction to Hybrid System
A hybrid system is a dynamical system that exhibits both continuous and discrete dynamic behavior – a system that can both flow (described by a differential equation) and jump (described by a state machine or automaton). Hybrid dynamical systems arise also when switching controllers are used to achieve stability and improve performance as . Typical examples of such systems are computer disk drives, constrained mechanical systems, switching power converters, and automotive powertrain applications.
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