NDLI: Scalable reinforcement learning through hierarchical decompositions for weakly-coupled problems

Content Provider	IEEE Xplore Digital Library
Author	Toutounji, H. Rothkopf, C.A. Triesch, J.
Copyright Year	2011
Description	Author affiliation: Frankfurt Institute for Advanced Studies, Germany (Toutounji, H.; Rothkopf, C.A.; Triesch, J.)
Abstract	Reinforcement Learning, or Reward-Dependent Learning, has been very successful at describing how animals and humans adjust their actions so as to increase their gains and reduce their losses in a wide variety of tasks. Empirical studies have furthermore identified numerous neuronal correlates of quantities necessary for such computations. But, in general it is too expensive for the brain to encode actions and their outcomes with respect to all available dimensions describing the state of the world. This suggests the existence of learning algorithms that are capable of taking advantage of the independencies present in the world and hence reducing the computational costs in terms of representations and learning. A possible solution is to use separate learners for task dimensions with independent dynamics and rewards. But the condition of independence is usually too restrictive. Here, we propose a hierarchical reinforcement learning solution for the more general case in which the dynamics are not independent but weakly coupled and show how to assign credit to the different modules, which solve the task jointly.
Starting Page	1
Ending Page	7
File Size	1277704
Page Count	7
File Format	PDF
ISBN	9781612849898
ISSN	21619484
e-ISBN	9781612849904
DOI	10.1109/DEVLRN.2011.6037351
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-24
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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