TY - GEN
T1 - Autoencoder-augmented neuroevolution for visual doom playing
AU - Alvernaz, Samuel
AU - Togelius, Julian
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/10/23
Y1 - 2017/10/23
N2 - Neuroevolution has proven effective at many re-inforcement learning tasks, including tasks with incomplete information and delayed rewards, but does not seem to scale well to high-dimensional controller representations, which are needed for tasks where the input is raw pixel data. We propose a novel method where we train an autoencoder to create a comparatively low-dimensional representation of the environment observation, and then use CMA-ES to train neural network controllers acting on this input data. As the behavior of the agent changes the nature of the input data, the autoencoder training progresses throughout evolution. We test this method in the VizDoom environment built on the classic FPS Doom, where it performs well on a health-pack gathering task.
AB - Neuroevolution has proven effective at many re-inforcement learning tasks, including tasks with incomplete information and delayed rewards, but does not seem to scale well to high-dimensional controller representations, which are needed for tasks where the input is raw pixel data. We propose a novel method where we train an autoencoder to create a comparatively low-dimensional representation of the environment observation, and then use CMA-ES to train neural network controllers acting on this input data. As the behavior of the agent changes the nature of the input data, the autoencoder training progresses throughout evolution. We test this method in the VizDoom environment built on the classic FPS Doom, where it performs well on a health-pack gathering task.
UR - http://www.scopus.com/inward/record.url?scp=85039980825&partnerID=8YFLogxK
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U2 - 10.1109/CIG.2017.8080408
DO - 10.1109/CIG.2017.8080408
M3 - Conference contribution
AN - SCOPUS:85039980825
T3 - 2017 IEEE Conference on Computational Intelligence and Games, CIG 2017
SP - 1
EP - 8
BT - 2017 IEEE Conference on Computational Intelligence and Games, CIG 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Conference on Computational Intelligence and Games, CIG 2017
Y2 - 22 August 2017 through 25 August 2017
ER -