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We introduce NATURAL PLAN, a realistic planning benchmark in natural language containing 3 key tasks: Trip Planning, Meeting Planning, and Calendar Scheduling.
Situations, actions, and causal laws
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Understanding natural language
Terry Winograd · 1972
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PDDL – The Planning Domain Definition Language
Drew McDermott, Malik Ghallab, Adele Howe, Craig Knoblock, A. Ram, Manuela Veloso, Daniel S. Weld, and David Wilkins · 1998
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The FF Planning System: Fast Plan Generation Through Heuristic Search
Jörg Hoffmann and Bernhard Nebel · 2001
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Automated Planning: Theory and Practice
Malik Ghallab, Dana Nau, and Paolo Traverso · 2004
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The first probabilistic track of the international planning competition
Håkan LS Younes, Michael L Littman, David Weissman, and John Asmuth · 2005
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The fast downward planning system
Malte Helmert · 2006
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Planning Algorithms
Steven M. LaValle · 2006
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Constrained model predictive control
Eduardo F Camacho, Carlos Bordons, Eduardo F Camacho, and Carlos Bordons · 2007
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Answer set programming at a glance
Gerhard Brewka, Thomas Eiter, and Mirosław Truszczyński · 2011
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Mobile robot planning using action language with an abstraction hierarchy
Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone · 2015
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Artificial intelligence: a modern approach
Stuart J Russell and Peter Norvig · 2016
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Platform-independent benchmarks for task and motion planning
Fabien Lagriffoul, Neil T Dantam, Caelan Garrett, Aliakbar Akbari, Siddharth Srivastava, and Lydia E Kavraki · 2018
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Task-motion planning for safe and efficient urban driving
Yan Ding, Xiaohan Zhang, Xingyue Zhan, and Shiqi Zhang · 2020
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
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Large language models cannot self-correct reasoning yet
Jie Huang, Xinyun Chen, Swaroop Mishra, Huaixiu Steven Zheng, Adams Wei Yu, Xinying Song, and Denny Zhou · 2023
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Llm+ p: Empowering large language models with optimal planning proficiency
Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, and Peter Stone · 2023
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Generalized planning in pddl domains with pretrained large language models
Tom Silver, Soham Dan, Kavitha Srinivas, Joshua B Tenenbaum, Leslie Pack Kaelbling, and Michael Katz · 2023
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Progprompt: Generating situated robot task plans using large language models
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, and Animesh Garg · 2023
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Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al · 2021
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Inner monologue: Embodied reasoning through planning with language models
Wenlong Huang, Fei Xia, Ted Xiao, Harris Chan, Jacky Liang, Pete Florence, Andy Zeng, Jonathan Tompson, Igor Mordatch, Yevgen Chebotar, et al · 2022
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Large language models still can’t plan (a benchmark for llms on planning and reasoning about change)
Karthik Valmeekam, Alberto Olmo, Sarath Sreedharan, and Subbarao Kambhampati · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Task and motion planning with large language models for object rearrangement
Yan Ding, Xiaohan Zhang, Chris Paxton, and Shiqi Zhang · 2023
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Reasoning with language model is planning with world model
Shibo Hao, Yi Gu, Haodi Ma, Joshua Jiahua Hong, Zhen Wang, Daisy Zhe Wang, and Zhiting Hu · 2023
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Task planning in robotics: an empirical comparison of pddl-and asp-based systems
Yu-qian Jiang, Shi-qi Zhang, Piyush Khandelwal, and Peter Stone
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Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
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Promptagent: Strategic planning with language models enables expert-level prompt optimization
Xinyuan Wang, Chenxi Li, Zhen Wang, Fan Bai, Haotian Luo, Jiayou Zhang, Nebojsa Jojic, Eric P Xing, and Zhiting Hu · 2023
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context, 2024
Google Gemini Team · 2024
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Leveraging pre-trained large language models to construct and utilize world models for model-based task planning
Lin Guan, Karthik Valmeekam, Sarath Sreedharan, and Subbarao Kambhampati · 2024
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On the planning abilities of large language models-a critical investigation
Karthik Valmeekam, Matthew Marquez, Sarath Sreedharan, and Subbarao Kambhampati · 2024
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Travelplanner: A benchmark for real-world planning with language agents
Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, and Yu Su · 2024
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Multi-robot planning with conflicts and synergies
Yuqian Jiang, Harel Yedidsion, Shiqi Zhang, Guni Sharon, and Peter Stone · 2032
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