Comparing Variable Handling Strategies in BDI Agents: Experimental Study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F24%3APU149873" target="_blank" >RIV/00216305:26230/24:PU149873 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fit.vut.cz/research/publication/13085/" target="_blank" >https://www.fit.vut.cz/research/publication/13085/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Comparing Variable Handling Strategies in BDI Agents: Experimental Study

Popis výsledku v původním jazyce

BDI (Belief-Desire-Intention) agents represent a paradigm in artificial intelligence, demonstrating proficiency in reasoning, planning, and decision-making. They offer a versatile framework to construct intelligent agents capable of reasoning about their beliefs, desires, and intentions. Our research focuses on AgentSpeak(L), a popular BDI language, and its interpreter using late variable bindings. Unlike traditional interpreters, it defers substitution selection until execution, enhancing rationality by preventing premature, erroneous selections. To validate our approach, we conducted experiments in a virtual collectable card marketplace. We implemented a system that can use both late and early variable binding strategies, comparing their performance. In shared and independent experiments, the late bindings strategy outperformed the early bindings strategy, although overhead costs were observed. We also conduct a brief discussion of the situations in which it is appropriate to use late b

Název v anglickém jazyce

Comparing Variable Handling Strategies in BDI Agents: Experimental Study

Popis výsledku anglicky

BDI (Belief-Desire-Intention) agents represent a paradigm in artificial intelligence, demonstrating proficiency in reasoning, planning, and decision-making. They offer a versatile framework to construct intelligent agents capable of reasoning about their beliefs, desires, and intentions. Our research focuses on AgentSpeak(L), a popular BDI language, and its interpreter using late variable bindings. Unlike traditional interpreters, it defers substitution selection until execution, enhancing rationality by preventing premature, erroneous selections. To validate our approach, we conducted experiments in a virtual collectable card marketplace. We implemented a system that can use both late and early variable binding strategies, comparing their performance. In shared and independent experiments, the late bindings strategy outperformed the early bindings strategy, although overhead costs were observed. We also conduct a brief discussion of the situations in which it is appropriate to use late b

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

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

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

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