- source
- (Tutum and 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
Tutum, Cem, and Risto Miikkulainen. 2020. “Adapting to Unseen Environments Through Explicit Representation of Context.” Artificial Life Conference Proceedings 32 (July). MIT Press:581–88.