LLM Reasoner and Automated Planner: A new NPC approach

Fuente: arXiv
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Autores principales: Puerta-Merino, Israel, Sabater-Mir, Jordi
Formato: Preprint
Publicado: 2025
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author Puerta-Merino, Israel
Sabater-Mir, Jordi
author_facet Puerta-Merino, Israel
Sabater-Mir, Jordi
contents In domains requiring intelligent agents to emulate plausible human-like behaviour, such as formative simulations, traditional techniques like behaviour trees encounter significant challenges. Large Language Models (LLMs), despite not always yielding optimal solutions, usually offer plausible and human-like responses to a given problem. In this paper, we exploit this capability and propose a novel architecture that integrates an LLM for decision-making with a classical automated planner that can generate sound plans for that decision. The combination aims to equip an agent with the ability to make decisions in various situations, even if they were not anticipated during the design phase.
format Preprint
id arxiv_https___arxiv_org_abs_2501_10106
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle LLM Reasoner and Automated Planner: A new NPC approach
Puerta-Merino, Israel
Sabater-Mir, Jordi
Artificial Intelligence
In domains requiring intelligent agents to emulate plausible human-like behaviour, such as formative simulations, traditional techniques like behaviour trees encounter significant challenges. Large Language Models (LLMs), despite not always yielding optimal solutions, usually offer plausible and human-like responses to a given problem. In this paper, we exploit this capability and propose a novel architecture that integrates an LLM for decision-making with a classical automated planner that can generate sound plans for that decision. The combination aims to equip an agent with the ability to make decisions in various situations, even if they were not anticipated during the design phase.
title LLM Reasoner and Automated Planner: A new NPC approach
topic Artificial Intelligence
url https://arxiv.org/abs/2501.10106