{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T21:03:44Z","timestamp":1775250224127,"version":"3.50.1"},"reference-count":83,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput. Soc. Syst."],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1109\/tcss.2025.3637527","type":"journal-article","created":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T21:18:20Z","timestamp":1771622300000},"page":"2514-2530","source":"Crossref","is-referenced-by-count":4,"title":["Embodied LLM Agents Learn to Cooperate in Organized Teams"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9607-2679","authenticated-orcid":false,"given":"Xudong","family":"Guo","sequence":"first","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-8634-3011","authenticated-orcid":false,"given":"Kaixuan","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1729-664X","authenticated-orcid":false,"given":"Jiale","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Penn State University, University Park, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0040-5759","authenticated-orcid":false,"given":"Wenhui","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6939-3282","authenticated-orcid":false,"given":"Natalia","family":"V\u00e9lez","sequence":"additional","affiliation":[{"name":"Department of Psychology, Princeton University, Princeton, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2949-1099","authenticated-orcid":false,"given":"Qingyun","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Information Science and Technology, Penn State University, University Park, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3918-6925","authenticated-orcid":false,"given":"Huazheng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, OR, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5138-7255","authenticated-orcid":false,"given":"Thomas L.","family":"Griffiths","sequence":"additional","affiliation":[{"name":"Department of Psychology, Princeton University, Princeton, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2101-9507","authenticated-orcid":false,"given":"Mengdi","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2024.3404039"},{"key":"ref2","first-page":"1","article-title":"Multi-agent graph reinforcement learning for connected automated driving","volume-title":"Proc. 37th Int. Conf. Mach. Learn. (ICML)","author":"Wang","year":"2020"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-019-1724-z"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3314139"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3070484"},{"key":"ref6","first-page":"3235","article-title":"Efficient communication in multi-agent reinforcement learning via variance based control","volume-title":"Proc. Adv. Neur. Inf. Process. Syst.","author":"Zhang","year":"2019"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2023\/15"},{"key":"ref8","first-page":"2145","article-title":"Learning to communicate with deep multi-agent reinforcement learning","author":"Foerster","year":"2016","journal-title":"Adv. Neur. Inf. Process. Syst."},{"key":"ref9","first-page":"1538","article-title":"Tarmac: Targeted multi-agent communication","volume-title":"Proc. Int. Conf. Mach. Learn","author":"Das","year":"2019"},{"key":"ref10","first-page":"12440","article-title":"Communication in multi-agent reinforcement learning: Intention sharing","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kim","year":"2020"},{"key":"ref11","first-page":"15230","article-title":"Learning to ground multi-agent communication with autoencoders","volume-title":"Proc. Adv. Neur. Inf. Process. Syst.","author":"Lin","year":"2021"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2024.3476030"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3586183.3606763"},{"key":"ref14","article-title":"MetaGPT: Meta programming for multi-agent collaborative framework","author":"Hong","year":"2023"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/icra57147.2024.10610855"},{"key":"ref16","article-title":"AgentVerse: Facilitating multi-agent collaboration and exploring emergent behaviors in agents","author":"Chen","year":"2023"},{"key":"ref17","article-title":"Training a helpful and harmless assistant with reinforcement learning from human feedback","author":"Bai","year":"2022"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00638"},{"key":"ref19","first-page":"31210","article-title":"Large language models can be easily distracted by irrelevant context","volume-title":"Proc. Int. Conf. Mach. Learn","author":"Shi","year":"2023"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.13"},{"key":"ref21","article-title":"Building cooperative embodied agents modularly with large language models","volume-title":"Proc. 12th Int. Conf. Learn. Representations","author":"Zhang","year":"2023"},{"key":"ref22","article-title":"Designing organizations for an information-rich world","volume":"72","author":"Simon","year":"1971","journal-title":"Comput., Commun., Public Interest"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-349-14540-9_7"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1111\/cogs.13232"},{"key":"ref25","article-title":"Autogen: Enabling next-gen LLM applications via multi-agent conversation framework","author":"Wu","year":"2023"},{"key":"ref26","volume-title":"Organizations","author":"March","year":"1958"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.2307\/2951495"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1525\/9780520352070"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.2307\/2118349"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1086\/317671"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1534702100"},{"key":"ref32","article-title":"Adaplanner: Adaptive planning from feedback with language models","author":"Sun","year":"2023"},{"key":"ref33","article-title":"Ghost in the minecraft: Generally capable agents for open-world enviroments via large language models with text-based knowledge and memory","author":"Zhu","year":"2023"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.507"},{"key":"ref35","article-title":"React: Synergizing reasoning and acting in language models","author":"Yao","year":"2022"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.52202\/075280-0377"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.52202\/075280-1988"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.52202\/068431-1800"},{"key":"ref39","article-title":"HuggingGPT: Solving AI tasks with chatgpt and its friends in huggingface","author":"Shen","year":"2023"},{"key":"ref40","article-title":"Gorilla: Large language model connected with massive apis","author":"Patil","year":"2023"},{"key":"ref41","article-title":"Voyager: An open-ended embodied agent with large language models","author":"Wang","year":"2023"},{"key":"ref42","first-page":"6382","article-title":"Multi-agent actor-critic for mixed cooperative-competitive environments","volume-title":"Proc. Adv. Neur. Inf. Process. Syst.","author":"Lowe","year":"2017"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.65109\/LVZZ5205"},{"key":"ref44","article-title":"Pommerman: A multi-agent playground","author":"Resnick","year":"2018"},{"key":"ref45","article-title":"Watch-and-help: A challenge for social perception and human-AI collaboration","author":"Puig","year":"2021"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-04105-y"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-60990-0_12"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-021-09996-w"},{"key":"ref49","first-page":"3040","article-title":"Social influence as intrinsic motivation for multi-agent deep reinforcement learning","volume-title":"Proc. Int. Conf. Machine Learn","author":"Jaques","year":"2019"},{"key":"ref50","article-title":"Language agents with reinforcement learning for strategic play in the werewolf game","author":"Xu","year":"2023"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.acl-long.782"},{"key":"ref52","first-page":"3474","article-title":"CAMEL: Communicative agents for \u201cmind\u201d exploration of large language model society","volume-title":"Proc. 37th Conf. Neural Inf. Process. Syst.","author":"Li","year":"2023"},{"key":"ref53","article-title":"Self-organized agents: A LLM multi-agent framework toward ultra large-scale code generation and optimization","author":"Ishibashi","year":"2024"},{"key":"ref54","article-title":"Metaagents: Simulating interactions of human behaviors for LLM-based task-oriented coordination via collaborative generative agents","author":"Li","year":"2023"},{"key":"ref55","article-title":"Multi-agent collaboration: Harnessing the power of intelligent LLM agents","author":"Talebirad","year":"2023"},{"key":"ref56","article-title":"Dynamic LLM-agent network: An LLM-agent collaboration framework with agent team optimization","author":"Liu","year":"2023"},{"key":"ref57","article-title":"Agents meet OKR: An object and key results driven agent system with hierarchical self-collaboration and self-evaluation","author":"Zheng","year":"2023"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.findings-naacl.448"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i16.29710"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/icra57147.2024.10610676"},{"key":"ref61","article-title":"Hierarchical auto-organizing system for open-ended multi-agent navigation","author":"Zhao","year":"2024"},{"key":"ref62","article-title":"S-agents: Self-organizing agents in open-ended environments","volume-title":"Proc. ICLR Workshop Large Lang. Model (LLM) Agents","author":"Chen","year":"2021"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.295"},{"key":"ref64","article-title":"Least-to-most prompting enables complex reasoning in large language models","author":"Zhou","year":"2022"},{"key":"ref65","article-title":"Universal and transferable adversarial attacks on aligned language models","author":"Zou","year":"2023"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i19.30150"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.346"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acllong.353"},{"key":"ref70","article-title":"Large language models as optimizers","author":"Yang","year":"2023"},{"key":"ref71","article-title":"Large language models are human-level prompt engineers","author":"Zhou","year":"2022"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.emnlp-main.494"},{"key":"ref73","first-page":"123","article-title":"Actor-critic algorithms","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Konda","year":"1999"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00886"},{"key":"ref75","first-page":"27730","article-title":"Training language models to follow instructions with human feedback","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"2022","author":"Ouyang"},{"key":"ref76","article-title":"Claude 3.5 sonnet","year":"2024"},{"key":"ref77","article-title":"Llama 2: Open foundation and fine-tuned chat models","author":"Touvron","year":"2023"},{"key":"ref78","article-title":"Introducing Llama 3.1: Our most capable models to date","year":"2024"},{"key":"ref79","volume-title":"The Future of Work","author":"Malone","year":"2004"},{"key":"ref80","first-page":"479","article-title":"Debating with more persuasive LLMS leads to more truthful answers","volume-title":"Proc. 41st Int. Conf. Mach. Learn.","author":"Khan","year":"2014"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1016\/j.cub.2021.03.090"},{"key":"ref82","article-title":"How far are we on the decision-making of LLMS? Evaluating LLMS\u2019 gaming ability in multi-agent environments","author":"Huang","year":"2024"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-025-58043-7"}],"container-title":["IEEE Transactions on Computational Social Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6570650\/11471691\/11402892.pdf?arnumber=11402892","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T19:56:00Z","timestamp":1775246160000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11402892\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":83,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tcss.2025.3637527","relation":{},"ISSN":["2329-924X","2373-7476"],"issn-type":[{"value":"2329-924X","type":"electronic"},{"value":"2373-7476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]}}}