Advanced Evaluation of Variable Binding Strategies in BDI Agents with Integrated Failure Handling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F26%3A0189429" target="_blank" >RIV/00216305:26230/26:0189429 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/book/10.1007/978-3-031-87327-0" target="_blank" >https://link.springer.com/book/10.1007/978-3-031-87327-0</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-87327-0_1" target="_blank" >10.1007/978-3-031-87327-0_1</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Advanced Evaluation of Variable Binding Strategies in BDI Agents with Integrated Failure Handling

Popis výsledku v původním jazyce

This paper explores Belief-Desire-Intention (BDI) agents, focusing on integrating late and early variable binding strategies in the AgentSpeak(L) language. We comprehensively evaluate these strategies by introducing novel experimental environments simulating a virtual marketplace and a robotic logistics system. Additionally, we integrate a CAN-based failure handling mechanism to test its impact on both binding strategies. Our findings show that the late binding strategy significantly enhances agent performance in complex, dynamic scenarios, especially when combined with failure handling. We also acknowledge and discuss the computational overheads associated with late bindings. This research advances the robustness and adaptability of BDI agents, demonstrating their potential for real-world applications.

Název v anglickém jazyce

Advanced Evaluation of Variable Binding Strategies in BDI Agents with Integrated Failure Handling

Popis výsledku anglicky

This paper explores Belief-Desire-Intention (BDI) agents, focusing on integrating late and early variable binding strategies in the AgentSpeak(L) language. We comprehensively evaluate these strategies by introducing novel experimental environments simulating a virtual marketplace and a robotic logistics system. Additionally, we integrate a CAN-based failure handling mechanism to test its impact on both binding strategies. Our findings show that the late binding strategy significantly enhances agent performance in complex, dynamic scenarios, especially when combined with failure handling. We also acknowledge and discuss the computational overheads associated with late bindings. This research advances the robustness and adaptability of BDI agents, demonstrating their potential for real-world applications.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

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

Název statě ve sborníku

Agents and Artificial Intelligence

ISBN

978-3-031-87326-3

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

27

Strana od-do

3-29

Název nakladatele

Springer Nature Switzerland AG

Místo vydání

Cham

Místo konání akce

Rome

Datum konání akce

24. 2. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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