loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Juan Carlos Saborío 1 and Joachim Hertzberg 2

Affiliations: 1 University of Osnabrück, Germany ; 2 University of Osnabrück and DFKI Robotics Innovation Center (Osnabrück), Germany

Keyword(s): Action Selection, Monte-Carlo Planning, Planning under Uncertainty.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Cognitive Systems ; Computational Intelligence ; Evolutionary Computing ; Soft Computing ; Symbolic Systems ; Task Planning and Execution ; Uncertainty in AI

Abstract: Task-planning algorithms for robots must quickly select actions with high reward prospects despite the huge variability of their domains, and accounting for the high cost of performing the wrong action in the “real-world”. In response we propose an action selection method based on reward-shaping, for planning in (PO)MDP’s, that adds an informed action-selection bias but depends almost exclusively on a clear specification of the goal. Combined with a derived rollout policy for MCTS planners, we show promising results in relatively large domains of interest to robotics.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.141.35.27

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Saborío, J. and Hertzberg, J. (2018). Towards Domain-independent Biases for Action Selection in Robotic Task-planning under Uncertainty. In Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-275-2; ISSN 2184-433X, SciTePress, pages 85-93. DOI: 10.5220/0006578500850093

@conference{icaart18,
author={Juan Carlos Saborío. and Joachim Hertzberg.},
title={Towards Domain-independent Biases for Action Selection in Robotic Task-planning under Uncertainty},
booktitle={Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2018},
pages={85-93},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006578500850093},
isbn={978-989-758-275-2},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Towards Domain-independent Biases for Action Selection in Robotic Task-planning under Uncertainty
SN - 978-989-758-275-2
IS - 2184-433X
AU - Saborío, J.
AU - Hertzberg, J.
PY - 2018
SP - 85
EP - 93
DO - 10.5220/0006578500850093
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic