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Planning has been part of the core pursuit for artificial intelligence since its conception, but earlier AI agents mostly focused on constrained settings because many of the cognitive substrates necessary for human-level planning have been lacking.
A cognitive model of planning
Hayes-Roth, B. and Hayes-Roth, F · 1979
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Robot planning
McDermott, D · 1992
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Dart: an example of accelerated evolutionary development
Cross, S. and Estrada, R · 1994
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Deep blue
Campbell, M., Hoane Jr, A. J., and Hsu, F.-h · 2002
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Planning and the brain
Grafman, J., Spector, L., and Rattermann, M. J · 2004
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Planning and scheduling in manufacturing and services
Pinedo, M · 2005
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Artificial intelligence a modern approach
Russell, S. J. and Norvig, P · 2010
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Htn planning: Overview, comparison, and beyond
Georgievski, I. and Aiello, M · 2015
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Solving general arithmetic word problems
Roy, S. and Roth, D · 2015
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Robot planning in the real world: Research challenges and opportunities
Alterovitz, R., Koenig, S., and Likhachev, M · 2016
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Mastering the game of go with deep neural networks and tree search
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al · 2016
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The predictron: End-to-end learning and planning
Silver, D., Hasselt, H., Hessel, M., Schaul, T., Guez, A., Harley, T., Dulac-Arnold, G., Reichert, D., Rabinowitz, N., Barreto, A., et al · 2017
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Language models are few-shot learners
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al · 2020
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Automated planning for robotics
Karpas, E. and Magazzeni, D · 2020
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Training verifiers to solve math word problems
Cobbe, K., Kosaraju, V., Bavarian, M., Chen, M., Jun, H., Kaiser, L., Plappert, M., Tworek, J., Hilton, J., Nakano, R., et al · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Nakano, R., Hilton, J., Balaji, S., Wu, J., Ouyang, L., Kim, C., Hesse, C., Jain, S., Kosaraju, V., Saunders, W., et al · 2021
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Are NLP models really able to solve simple math word problems?
Patel, A., Bhattamishra, S., and Goyal, N · 2021
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Language models as agent models
Andreas, J · 2022
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Planning with theory of mind
Ho, M. K., Saxe, R., and Cushman, F · 2022
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Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
Huang, W., Abbeel, P., Pathak, D., and Mordatch, I · 2022
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Do as I can, not as I say: Grounding language in robotic affordances
Ichter, B., Brohan, A., Chebotar, Y., Finn, C., Hausman, K., Herzog, A., Ho, D., Ibarz, J., Irpan, A., Jang, E., Julian, R., Kalashnikov, D., Levine, S., Lu, Y., Parada, C., Rao, K., Sermanet, P., Toshev, A., Vanhoucke, V., Xia, F., Xiao, T., Xu, P., Yan, M., Brown, N., Ahn, M., Cortes, O., Sievers, N., Tan, C., Xu, S., Reyes, D., Rettinghouse, J., Quiambao, J., Pastor, P., Luu, L., Lee, K., Kuang, Y., Jesmonth, S., Joshi, N. J., Jeffrey, K., Ruano, R. J., Hsu, J., Gopalakrishnan, K., David, B., Zeng, A., and Fu, C. K · 2022
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Solving quantitative reasoning problems with language models
Lewkowycz, A., Andreassen, A., Dohan, D., Dyer, E., Michalewski, H., Ramasesh, V. V., Slone, A., Anil, C., Schlag, I., Gutman-Solo, T., Wu, Y., Neyshabur, B., Gur-Ari, G., and Misra, V · 2022
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Planning in the brain
Mattar, M. G. and Lengyel, M · 2022
Cited alongside, same era.
Chatgpt, 2022
OpenAI · 2022
Cited alongside, same era.
Chain-of-thought prompting elicits reasoning in large language models
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Xia, F., Chi, E., Le, Q. V., Zhou, D., et al · 2022
Cited alongside, same era.
React: Synergizing reasoning and acting in language models
Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K. R., and Cao, Y · 2022
Cited alongside, same era.
Autogpt, 2023
AutoGPT · 2023
Cited alongside, same era.
Graph of thoughts: Solving elaborate problems with large language models
Besta, M., Blach, N., Kubicek, A., Gerstenberger, R., Gianinazzi, L., Gajda, J., Lehmann, T., Podstawski, M., Niewiadomski, H., Nyczyk, P., et al · 2023
Cited alongside, same era.
Reflexion: Language agents with verbal reinforcement learning
Shinn, N., Cassano, F., Gopinath, A., Narasimhan, K. R., and Yao, S · 2023
Later among the works it cites.
Llm-planner: Few-shot grounded planning for embodied agents with large language models
Song, C. H., Wu, J., Washington, C., Sadler, B. M., Chao, W.-L., and Su, Y · 2023
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Language agents: a critical evolutionary step of artificial intelligence
Su, Y · 2023
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Cognitive architectures for language agents
Sumers, T. R., Yao, S., Narasimhan, K., and Griffiths, T. L · 2023
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Planbench: An extensible benchmark for evaluating large language models on planning and reasoning about change
Valmeekam, K., Olmo, A., Sreedharan, S., and Kambhampati, S · 2023
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Walking down the memory maze: Beyond context limit through interactive reading
Chen, H., Pasunuru, R., Weston, J., and Celikyilmaz, A · 2023
Cited alongside, same era.
Mind2web: Towards a generalist agent for the web
Deng, X., Gu, Y., Zheng, B., Chen, S., Stevens, S., Wang, B., Sun, H., and Su, Y · 2023
Cited alongside, same era.
Gemini: a family of highly capable multimodal models
G Team, G., Anil, R., Borgeaud, S., Wu, Y., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., et al · 2023
Cited alongside, same era.
Openagi: When llm meets domain experts
Ge, Y., Hua, W., Ji, J., Tan, J., Xu, S., and Zhang, Y · 2023
Cited alongside, same era.
Jiang, A. Q., Sablayrolles, A., Mensch, A., Bamford, C., Chaplot, D. S., Casas, D. d. l., Bressand, F., Lengyel, G., Lample, G., Saulnier, L., et al · 2023
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Api-bank: A comprehensive benchmark for tool-augmented llms
Li, M., Zhao, Y., Yu, B., Song, F., Li, H., Yu, H., Li, Z., Huang, F., and Li, Y · 2023
Cited alongside, same era.
Wang, G., Xie, Y., Jiang, Y., Mandlekar, A., Xiao, C., Zhu, Y., Fan, L., and Anandkumar, A · 2023
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Llm-powered autonomous agents
Weng, L · 2023
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Openagents: An open platform for language agents in the wild
Xie, T., Zhou, F., Cheng, Z., Shi, P., Weng, L., Liu, Y., Hua, T. J., Zhao, J., Liu, Q., Liu, C., Liu, L. Z., Xu, Y., Su, H., Shin, D., Xiong, C., and Yu, T · 2023
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On the tool manipulation capability of open-source large language models
Xu, Q., Hong, F., Li, B., Hu, C., Chen, Z., and Zhang, J · 2023
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Tree of thoughts: Deliberate problem solving with large language models
Yao, S., Yu, D., Zhao, J., Shafran, I., Griffiths, T. L., Cao, Y., and Narasimhan, K. R · 2023
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Distilling script knowledge from large language models for constrained language planning
Yuan, S., Chen, J., Fu, Z., Ge, X., Shah, S., Jankowski, C., Xiao, Y., and Yang, D · 2023
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Memorybank: Enhancing large language models with long-term memory
Zhong, W., Guo, L., Gao, Q., and Wang, Y · 2023
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Recurrentgpt: Interactive generation of (arbitrarily) long text
Zhou, W., Jiang, Y. E., Cui, P., Wang, T., Xiao, Z., Hou, Y., Cotterell, R., and Sachan, M · 2023
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ToolQA: A dataset for LLM question answering with external tools
Zhuang, Y., Yu, Y., Wang, K., Sun, H., and Zhang, C · 2023
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Jiang, A. Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D. S., de las Casas, D., Hanna, E. B., Bressand, F., Lengyel, G., Bour, G., Lample, G., Lavaud, L. R., Saulnier, L., Lachaux, M.-A., Stock, P., Subramanian, S., Yang, S., Antoniak, S., Scao, T. L., Gervet, T., Lavril, T., Wang, T., Lacroix, T., and Sayed, W. E · 2024
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Agentbench: Evaluating llms as agents
Liu, X., Yu, H., Zhang, H., Xu, Y., Lei, X., Lai, H., Gu, Y., Ding, H., Men, K., Yang, K., et al · 2024
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Toolllm: Facilitating large language models to master 16000+ real-world apis
Qin, Y., Liang, S., Ye, Y., Zhu, K., Yan, L., Lu, Y., Lin, Y., Cong, X., Tang, X., Qian, B., et al · 2024
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Timearena: Shaping efficient multitasking language agents in a time-aware simulation
Zhang, Y., Yuan, S., Hu, C., Richardson, K., Xiao, Y., and Chen, J · 2024
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Gpt-4v(ision) is a generalist web agent, if grounded
Zheng, B., Gou, B., Kil, J., Sun, H., and Su, Y · 2024
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Webarena: A realistic web environment for building autonomous agents
Zhou, S., Xu, F. F., Zhu, H., Zhou, X., Lo, R., Sridhar, A., Cheng, X., Bisk, Y., Fried, D., Alon, U., et al · 2024
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Toolchain*: Efficient action space navigation in large language models with a* search
Zhuang, Y., Chen, X., Yu, T., Mitra, S., Bursztyn, V., Rossi, R. A., Sarkhel, S., and Zhang, C · 2024
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