Adapting to Unseen Environments through Explicit Representation of Context by Tutum, C., & Miikkulainen, R. (2020)

source
(Tutum, Miikkulainen 2020)
tags
Meta-learning, Reinforcement learning, ALife 2020

Summary

This work introduces the idea of Context-Skill networks for continuous RL tasks. Experiments are done on a Flappy bird like game.

The authors use a LSTM as a context network to make part of the prediction and a feed-forward neural network as a skill network. They are able to demonstrate that in that game, better performances are achieved by using both networks compared to a single one.

Bibliography

  1. . . "Adapting to Unseen Environments Through Explicit Representation of Context". Artificial Life Conference Proceedings 32 (July). MIT Press:581–88. DOI.
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