[vc_row el_class=”inner-body-content” css=”.vc_custom_1667210837820{padding-top: 30px !important;padding-bottom: 20px !important;}”][vc_column][vc_custom_heading text=”COURSE OBJECTIVES” use_theme_fonts=”yes” css=”.vc_custom_1667210846129{margin-top: 0px !important;}”][vc_column_text]
- To study the applications of AI and agent based approach to AI.
- To study first-order predicate calculus, logical reasoning and problem solving using Prolog language.
- To study and discuss various techniques and algorithms of AI used in general problem solving, optimization problems, constraint satisfaction problems, and game programming.
- To familiarize students with various sub-areas of AI, such as expert systems, natural language processing and machine learning.
[/vc_column_text][vc_custom_heading text=”COURSE LEARNING OUTCOMES (CLO)” font_container=”tag:h3|text_align:left” use_theme_fonts=”yes”][vc_column_text]CLO: 1. Explain artificial intelligence, its characteristics and its application areas. (C1-Knowledge)
CLO: 2. Formulate real-world problems as state space problems, optimization problems or constraint satisfaction problems. (C4-Analysis)
CLO: 3. Select and apply appropriate algorithms and AI techniques to solve complex problems. (C3-Application)
CLO: 4. Design and develop an expert system by using appropriate tools and techniques. (C3-Application)
[/vc_column_text][vc_custom_heading text=”COURSE CONTENTS” use_theme_fonts=”yes”][vc_column_text css=”.vc_custom_1667210817719{margin-bottom: 0px !important;}”]
- Defining AI; Turing’s test; Weak vs. Strong AI.
- Applications of AI; Agent based approach
- State space search: DFS, BFS, IDS algorithms
- Informed search: A* algorithm
- Optimization problems & Local search algorithms
- Genetic algorithms
- Constraint satisfaction problems
- Expert systems
- Game playing (adversarial search)
- Introduction to machine learning
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