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Norm Augmented Reinforcement Learning Agents With Synthesized Normative Rules: A Proposed Normative Agent Framework

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F24%3A50021597" target="_blank" >RIV/62690094:18450/24:50021597 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.igi-global.com/gateway/article/345650" target="_blank" >https://www.igi-global.com/gateway/article/345650</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.4018/JCIT.345650" target="_blank" >10.4018/JCIT.345650</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Norm Augmented Reinforcement Learning Agents With Synthesized Normative Rules: A Proposed Normative Agent Framework

  • Original language description

    The dynamic deontic (DD) is a norm synthesis framework that extracts normative rules from reinforcement learning (RL), however it was not designed to be applied in agent coordination. This study proposes a norm augmented reinforcement learning framework (NARLF) that extends said model to include a norm deliberation mechanism for learned norms re-imputation for norm biased decision-making RL agents. This study aims to test the effects of synthesized norms applied on-line and off-line on agent learning performance. The framework consists of the DD framework extended with a pre-processing and deliberation component to allow re-imputation of normative rules. A deliberation model, the Norm Augmented Q-Table (NAugQT), is proposed to map normative rules into RL agents via q-values weight updates. Results show that the framework is able to map and improve RL agent’s performance but only when synthesized off-line edited absolute norm salience value norms are used. This shows limitations when unstable salience norms are applied. Improvement in norm extraction and pre-processing are required. © 2024 IGI Global. All rights reserved.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Journal of Cases on Information Technology

  • ISSN

    1548-7717

  • e-ISSN

    1548-7725

  • Volume of the periodical

    26

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    34

  • Pages from-to

    1-34

  • UT code for WoS article

    001283032700001

  • EID of the result in the Scopus database

    2-s2.0-85199374981