CS188.1x-Artificial-Intelligence (edX)

These are the assigments for the 02.2015 edX/BerkleyX course found here: https://www.edx.org/course/artificial-intelligence-uc-berkeleyx-cs188-1x-0

Project 1

• Depth First Search (DFS)
• Breadth First Search (BFS)
• Uniform Cost Search (UCS)
• A star Search (A*)
• Various Heuristics

Files edited:

• search.py
• searchAgents.py

Project 2

• Evaluation function for a reflex agent
• Minimax with multiple adversaries
• Alpha Beta pruning
• Expectimax with average
• An evaluation function for states (instead of actions)

Files edited:

• multiAgents.py

Project 3

• Value iteration offline planning agent
• Policy calculation and parameters
• Q-Learning
• Epsilon greedy (q-learning)
• Approximate q-learning and state abstraction
• Approximate q-learning with features and weights

Files edited:

• analysis.py
• qlearningAgents.py
• valueIterationAgents.py

Useful commands can be found under Project xx\commands.txt