MCTS on model-based Bayesian Reinforcement Learning for efficient learning in Partially Observable environments

Sammie Katt; Frans Oliehoek; Christopher Amato

MCTS on model-based Bayesian Reinforcement Learning for efficient learning in Partially Observable environments

Sammie Katt, Frans Oliehoek, Christopher Amato

Interactive Intelligence

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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Original language	English
Title of host publication	NeurIPS Workshop on Reinforcement Learning under Partial Observability
Pages	1-3
Number of pages	3
Publication status	Published - 2018
Event	NIPS 2018: 32nd Conference on Neural Information Processing Systems - Montréal, Canada Duration: 3 Dec 2018 → 8 Dec 2018 Conference number: 32

Conference

Conference	NIPS 2018
Country/Territory	Canada
City	Montréal
Period	3/12/18 → 8/12/18

Bibliographical note

Accepted author manuscript

Access to Document

Katt18RLPOAccepted author manuscript, 240 KB

https://sites.google.com/site/rlponips2018/home/accepted-papers

Cite this

@inproceedings{cda5fff8b2214d7c938cd69758730e89,

title = "MCTS on model-based Bayesian Reinforcement Learning for efficient learning in Partially Observable environments",

author = "Sammie Katt and Frans Oliehoek and Christopher Amato",

note = "Accepted author manuscript; NIPS 2018 : 32nd Conference on Neural Information Processing Systems ; Conference date: 03-12-2018 Through 08-12-2018",

year = "2018",

language = "English",

pages = "1--3",

booktitle = "NeurIPS Workshop on Reinforcement Learning under Partial Observability",

}

MCTS on model-based Bayesian Reinforcement Learning for efficient learning in Partially Observable environments. / Katt, Sammie; Oliehoek, Frans; Amato, Christopher.
NeurIPS Workshop on Reinforcement Learning under Partial Observability. 2018. p. 1-3.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - MCTS on model-based Bayesian Reinforcement Learning for efficient learning in Partially Observable environments

AU - Katt, Sammie

AU - Oliehoek, Frans

AU - Amato, Christopher

N1 - Conference code: 32

PY - 2018

Y1 - 2018

M3 - Conference contribution

SP - 1

EP - 3

BT - NeurIPS Workshop on Reinforcement Learning under Partial Observability

T2 - NIPS 2018

Y2 - 3 December 2018 through 8 December 2018

ER -