loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: George Mason 1 ; Radu Calinescu 1 ; Daniel Kudenko 1 and Alec Banks 2

Affiliations: 1 University of York, United Kingdom ; 2 Defence Science and Technology Laboratory, United Kingdom

Keyword(s): Reinforcement Learning, Safety Constraint Verification, Abstract Markov Decision Processes.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Computational Intelligence ; Constraint Satisfaction ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Privacy, Safety and Security ; Soft Computing ; Symbolic Systems ; Uncertainty in AI

Abstract: We present a new reinforcement learning (RL) approach that enables an autonomous agent to solve decision making problems under constraints. Our assured reinforcement learning approach models the uncertain environment as a high-level, abstract Markov decision process (AMDP), and uses probabilistic model checking to establish AMDP policies that satisfy a set of constraints defined in probabilistic temporal logic. These formally verified abstract policies are then used to restrict the RL agent's exploration of the solution space so as to avoid constraint violations. We validate our RL approach by using it to develop autonomous agents for a flag-collection navigation task and an assisted-living planning problem.

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 18.191.240.243

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:
Mason, G.; Calinescu, R.; Kudenko, D. and Banks, A. (2017). Assured Reinforcement Learning with Formally Verified Abstract Policies. In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-220-2; ISSN 2184-433X, SciTePress, pages 105-117. DOI: 10.5220/0006156001050117

@conference{icaart17,
author={George Mason. and Radu Calinescu. and Daniel Kudenko. and Alec Banks.},
title={Assured Reinforcement Learning with Formally Verified Abstract Policies},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2017},
pages={105-117},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006156001050117},
isbn={978-989-758-220-2},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Assured Reinforcement Learning with Formally Verified Abstract Policies
SN - 978-989-758-220-2
IS - 2184-433X
AU - Mason, G.
AU - Calinescu, R.
AU - Kudenko, D.
AU - Banks, A.
PY - 2017
SP - 105
EP - 117
DO - 10.5220/0006156001050117
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