Finding intrinsic rewards by embodied evolution and constrained reinforcement learning
type: Item
instance of: scholarly article
title: Finding intrinsic rewards by embodied evolution and constrained reinforcement learning
zbMATH Open document ID: 1254.68267
author: Eiji Uchibe
author: Kenji Doya
published in: Neural Networks
publication date: 2013-01-17T00:00:00Z
Mathematics Subject Classification ID: 68T40
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 6126382
zbMATH Keywords: intrinsic and extrinsic rewards
zbMATH Keywords: reinforcement learning
zbMATH Keywords: embodied evolution
zbMATH Keywords: cyber rodents
Wikidata QID: Q47232670
MaRDI profile type: Publication
full work available at URL: j.neunet.2008.09.013
OpenAlex ID: W1974142402
cites work: Q4533362
cites work: Q4436854
cites work: Guiding exploration by pre-existing knowledge without modifying reward
cites work: OnActor-Critic Algorithms
DOI: 10.1016/J.NEUNET.2008.09.013
description: scientific article; zbMATH DE number 6126382