Supplementary information files for Context meta-reinforcement learning via neuromodulation

Supplementary files for article Context meta-reinforcement learning via neuromodulation Meta-reinforcement learning (meta-RL) algorithms enable agents to adapt quickly to tasks from few samples in dynamic environments. Such a feat is achieved through dynamic representations in an agent’s policy netw...

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Bibliographic Details

Main Authors:	Eseoghene Ben-Iwhiwhu, Jeffery Dick, Nicholas A Ketz, Praveen K Pilly, Andrea Soltoggio
Format:	Data Data
Published:	2023
Subjects:	Meta-learning Lifelong-learning Deep reinforcement learning Neuromodulation
Online Access:	https://dx.doi.org/10.17028/rd.lboro.23592483.v1
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