392209 ISY Project: Deep Reinforcement Learning (Pj) (WiSe 2019/2020)

The emerging field of deep reinforcement learning has led to remarkable empirical results in rich and varied domains like robotics, arcade games, and multiagent interaction. In this project, you will gain practical experience with Deep Learning Architectures for AI in simulated environments, apply neural networks to learn and produce complex purposeful actions in the context of one of the following environments on your choice [1-13]

[1] https://youtu.be/XjsY8-P4WHM (Atari)
[2] https://www.pommerman.com
[3] https://gym.openai.com/envs/MontezumaRevenge-v0
[4] http://vizdoom.cs.put.edu.pl
[5] https://www.crowdai.org/challenges/marlo-2018
[6] https://www.crowdai.org/challenges/neurips-2018-ai-for-prosthetics-challenge
[7] https://youtu.be/Ul0Gilv5wvY (PFNN)
[8] https://youtu.be/vppFvq2quQ0 (DeepMimic)
[9] https://github.com/MarkPKCollier/NeuralTuringMachine
[10] https://github.com/brendenlake/BPL (one-shot learning)
[11] https://github.com/Unity-Technologies/obstacle-tower-env
[12] https://www.youtube.com/watch?v=-L4tCIGXKBE (Differentiable Physics for Tool-Use and Manipulation Planning)
[13] https://www.crowdai.org/challenges/neurips-2018-ai-for-prosthetics-challenge

Requirements for participation, required level

Required skills:
Introduction to Neural Networks course or Advanced Neural Networks
Python or C++ (>= 1 year)

Bibliography

https://rebrand.ly/DRL