Artificial Intelligence Computer Science Course Information Difficulty: Intermediate Categories: Bachelor of Engineering : CS and IT, BCA, BE, BSc Computer Science Tags: Adaboost ensemble learning algorithm, adaptive dynamic programming, Algorithm, Artifical Intelligence, best-first search algorithm, BFS, Breadth First Search, Breadth first search algorithm, decision tree learning, decision tree learning algorithm for the restaurant waiting problem, deep depth first search, Depth First Search, DFS, e reinforcement learning algorithm, feed forward back propagation neural network learning algorithm, Iterative deep depth first search, Naive Bayes’ learning algorithm, passive reinforcement learning algorithm, passive reinforcement learning algorithm based on temporal differences (TD), recursive best-first search algorithm, Romanian map problem, temporal differences (TD) Course Instructor Dr.Mahendra Kanojia Author Join this Course FREE Practical Practical 1: Aim: Implement Breadth first search algorithm for Romanian map problem. Practical 2: Aim: Implement Iterative deep depth first search for Romanian map problem. Practical 3: Aim: Implement A* search algorithm for Romanian map problem. Practical 4: Aim: Implement recursive best-first search algorithm for Romanian map problem. Practical 5: Aim: Implement decision tree learning algorithm for the restaurant waiting problem. Practical 6: Aim: Implement feed forward back propagation neural network learning algorithm for the restaurant waiting problem. Practical 7: Aim: Implement Adaboost ensemble learning algorithm for the restaurant waiting problem. Practical 8: Aim: Implement Naive Bayes’ learning algorithm for the restaurant waiting problem. Practical 9: Aim: Implement passive reinforcement learning algorithm based on adaptive dynamic programming (ADP) for the 3 by 4 world problem Leave a Reply Cancel replyYour email address will not be published. Required fields are marked *Name * Email * Website Comment *
