When Prolog meets generative models: a new approach for managing knowledge and planning in robotic applications
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Abstract (arXiv)
In this paper, we propose a robot oriented knowledge management system based on the use of the Prolog language. Our framework hinges on a special organisation of knowledge base that enables: 1. its efficient population from natural language texts using semi-automated procedures based on Large Language Models, 2. the bumpless generation of temporal parallel plans for multi-robot systems through a sequence of transformations, 3. the automated translation of the plan into an executable formalism (the behaviour trees). The framework is supported by a set of open source tools and is shown on a realistic application.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 12 of its 33 references that are in the map. First posted on arXiv 26 Sep 2023.
Builds on
12 of 33 references.
References · 12
- 2017Attention Is All You Needcited by 60,361
- 2023GPT-4 Technical Reportcited by 18,396
- 2023A Survey of Large Language Modelscited by 2,576
- 2022Code as Policies: Language Model Programs for Embodied Controlcited by 1,210
- 2023PaLM 2 Technical Reportcited by 1,162
- 2019Neural Probabilistic Logic Programming in DeepProbLogcited by 394
- 2022Talking About Large Language Modelscited by 175
- 2020A Survey of Behavior Trees in Robotics and AIcited by 55
- 2018A Survey of Knowledge Representation in Service Roboticscited by 18
- 2014COLIN: Planning with Continuous Linear Numeric Changecited by 10
- 2021PlanSys2: A Planning System Framework for ROS2cited by 6
- 2022Understanding Natural Language in Contextcited by 1
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Citing papers per year: 2025: 2.
2 papers.