- which is runnable either using Anaconda's Jupyter Notebook or using Google Colabs
- The 24-puzzle problem
- Breadth-first search (BFS)
- Depth-first search (DFS)
- Informed search algorithms using
- h1(x) = number of misplaced tiles
- h2(x) = sum of the distances of every tile to its goal position.
- Find the global minimum of the Eggholder’s Function
- Using Hill Climbing Search.
- Using Differential Evolution.
- Find a solution of the N-queens problem
- Using Hill Climbing Search.
- Using Genetic Algorithm.
- Your task is to write an AI program to solve the Sudoku puzzle as a constraint satisfaction problem.
- Naïve Backtracking Algorithm
- Smart Backtracking Algorithm
- Your task is to write an AI program to play Othello with a human player. Your tasks include
- Implement an Othello playing interface that one can play the game.
- Design a heuristic function for the intermediate states.
- Design a pattern recognition neural network to recognize handwriting digits (0-9).
- Encode the data into input and target files for neural network training.
- Train the neural network (pattern net) based on your input/output files.
- The project is one of Kaggle’s past challenge “Traveling Santa 2018 - Prime Paths.” https://www.kaggle.com/c/traveling-santa-2018-prime-paths/
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Problem Definition. Simply describe the “Traveling Santa Problem – Prime Paths” problem.
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Methods Provide detailed description on your methods, implementation details (pseudo code, flow chart, etc.),
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Results Analyze the results you get, for example, how do methods/strategies lead to a better solution? What do you learn from this project? Use figures, charts, and tables to assist your analysis. You can also compare your results with the Kaggle winners.
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Conclusions Provide your conclusions. Do you achieve your goal? Why or why not? If there a way to do it better?
React
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Facebook
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