Advanced Artificial Intelligence

CS6955: Advanced Artificial Intelligence, University of Utah, Spring 2026.

Installation

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Structure

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├── algorithm   # algorithm implementations
│   └── config      # configuration files for algorithms
├── docs        # reports
├── environment # environment setup
├── model       # model implementations (mlp, cnn, etc.)
├── script      # scripts for running tasks
└── util        # utility and helper functions

Algorithms

#	Abbr	Algorithm
1	bc	Behavioral Cloning
2	bco	Behavioral Cloning from Observation
3	q	Q-Learning
4	dqn	Deep Q-Network
5	vpg	Vanilla Policy Gradient
6	ppo	PPO

Usage

# Run algorithms on Gym environments
python run.py
# Manually play Gym environments
python play.py

References

• Class Website
• Reinforcement Learning: An Introduction
• OpenAI Spinning Up

Homeworks

1. Imitation Learning
2. Advanced BC and Interactive Imitation Learning
3. Multi-Armed Bandits
4. Q-Learning and DQN
5. Policy Gradient