This is a report including all projects in my 2019 Fall Artificial Intelligence course (DATA130008.01) in School of Data Science of Fudan University . The project is mainly adapted from UCB CS118 and Stanford CS231.
Project1-Pacman
- In this project, my Pacman agent will find paths through the maze world, both to reach a particular location and to collect food efficiently. I will build general search algorithms and apply them to Pacman scenarios. (Key words: DFS, BFS, UCS, A* Search, Heuristic function, Greedy)
- You can see the detail of project here and my report here
Project2_Nqueens
- In this project, I am going to construct a CSP for N-Queens problem.(Key words: Backtracking, CSP, AC-3)
- You can see the detail of project here and my report here
Project3_Blackjack
- In this project, I implement algorithms to find the optimal policy in some situations, also I formalize a modified version of Blackjack as an MDP, and apply the algorithm to find the optimal policy.(Key words: MDP)
- You can see the detail of project here and my report here
Project4_Cars
- This project is a modified version of the Driverless Car assignment written by Chris Piech.
- In this project, I focus on the sensing system, which allows us to track other cars based on noisy sensor readings.(Key words: Bayesian network basics, Emission probabilities, Transition probabilities, Particle filtering)
- You can see the detail of project here and my report here
FinalProject_GOMOKU
- I do this project with Ruipu Luo
- In this project, we design a fast and effective search algorithm for Gomoku playing.
- We use MCTS and Minimax search with
$\alpha$ -$\beta$ pruning algorithm for Gomoku and add the threat space algorithm to directly find those high-threat points in order to save search time. The pruning algorithm can reach the chess power of pisq7, which won the 24th place in the Gomoku AI Contest 2015. - You can see the detail of project here and my report here