Open Access
Open access
Lecture Notes in Computer Science, volume 13067 LNAI, pages 108-120

Long-Term Exploration in Persistent MDPs

Publication typeBook Chapter
Publication date2021-10-20
Quartile SCImago
Q3
Quartile WOS
Impact factor
ISSN03029743, 16113349, 18612075, 18612083
Abstract
Exploration is an essential part of reinforcement learning, which restricts the quality of learned policy. Hard-exploration environments are defined by huge state space and sparse rewards. In such conditions, an exhaustive exploration of the environment is often impossible, and the successful training of an agent requires a lot of interaction steps. In this paper, we propose an exploration method called Rollback-Explore (RbExplore), which utilizes the concept of the persistent Markov decision process, in which agents during training can roll back to visited states. We test our algorithm in the hard-exploration Prince of Persia game, without rewards and domain knowledge. At all used levels of the game, our agent outperforms or shows comparable results with state-of-the-art curiosity methods with knowledge-based intrinsic motivation: ICM and RND. An implementation of RbExplore can be found at https://github.com/cds-mipt/RbExplore .

Citations by journals

1
Neural Computing and Applications
Neural Computing and Applications, 1, 100%
Neural Computing and Applications
1 publication, 100%
1

Citations by publishers

1
Springer Nature
Springer Nature, 1, 100%
Springer Nature
1 publication, 100%
1
  • We do not take into account publications that without a DOI.
  • Statistics recalculated only for publications connected to researchers, organizations and labs registered on the platform.
  • Statistics recalculated weekly.
Metrics
Share
Cite this
GOST |
Cite this
GOST Copy
Ugadiarov L. et al. Long-Term Exploration in Persistent MDPs // Lecture Notes in Computer Science. 2021. Vol. 13067 LNAI. pp. 108-120.
GOST all authors (up to 50) Copy
Ugadiarov L., Skrynnik A., Panov A. Long-Term Exploration in Persistent MDPs // Lecture Notes in Computer Science. 2021. Vol. 13067 LNAI. pp. 108-120.
RIS |
Cite this
RIS Copy
TY - GENERIC
DO - 10.1007/978-3-030-89817-5_8
UR - https://doi.org/10.1007%2F978-3-030-89817-5_8
TI - Long-Term Exploration in Persistent MDPs
T2 - Lecture Notes in Computer Science
AU - Ugadiarov, Leonid
AU - Skrynnik, Alexey
AU - Panov, Aleksandr
PY - 2021
DA - 2021/10/20 00:00:00
PB - Springer Nature
SP - 108-120
VL - 13067 LNAI
SN - 0302-9743
SN - 1611-3349
SN - 1861-2075
SN - 1861-2083
ER -
BibTex
Cite this
BibTex Copy
@incollection{2021_Ugadiarov
author = {Leonid Ugadiarov and Alexey Skrynnik and Aleksandr Panov},
title = {Long-Term Exploration in Persistent MDPs},
publisher = {Springer Nature},
year = {2021},
volume = {13067 LNAI},
pages = {108--120},
month = {oct}
}
Found error?