Project 1: Search
Implement the DFS, BFS, UFS and A* search algorithms
Project 2: Multiagent Search
Implement multiagent minimax and expectimax algorithms, as well as designing evaluation functions
Project 3: Tracking
Probabilistic inference on Bayes Nets and the forward algorithm and particle sampling in a Hidden Markov Model
Project 4: Reinforcement Learning
Implement Value Function, Q learning, and Approximate Q learning
Project 5: Machine Learning
Implement the perceptron algorithm, neural network, and recurrent nn models.
Apply the models to several tasks including digit classification and language identification.
UC Berkeley: CS188 2022 SU