LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents

التفاصيل البيبلوغرافية
العنوان: LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents
المؤلفون: Choi, Jae-Woo, Yoon, Youngwoo, Ong, Hyobin, Kim, Jaehong, Jang, Minsu
سنة النشر: 2024
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Artificial Intelligence
الوصف: Large language models (LLMs) have recently received considerable attention as alternative solutions for task planning. However, comparing the performance of language-oriented task planners becomes difficult, and there exists a dearth of detailed exploration regarding the effects of various factors such as pre-trained model selection and prompt construction. To address this, we propose a benchmark system for automatically quantifying performance of task planning for home-service embodied agents. Task planners are tested on two pairs of datasets and simulators: 1) ALFRED and AI2-THOR, 2) an extension of Watch-And-Help and VirtualHome. Using the proposed benchmark system, we perform extensive experiments with LLMs and prompts, and explore several enhancements of the baseline planner. We expect that the proposed benchmark tool would accelerate the development of language-oriented task planners.
Comment: ICLR 2024. Code: https://github.com/lbaa2022/LLMTaskPlanning
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2402.08178
رقم الأكسشن: edsarx.2402.08178
قاعدة البيانات: arXiv