Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems
As artificial intelligence increasingly permeates everyday life, the development of Large Language Models (LLMs) capable of effectively simulating complex social interactions and fostering cooperative behavior has become paramount. This paper explores the enhancement of cooperative capabilities in L...
- Autores:
-
Ortiz Almanza, David Santiago
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2024
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/74464
- Acceso en línea:
- https://hdl.handle.net/1992/74464
- Palabra clave:
- Communication
Cooperation
Artificial intelligence
Large language models
Melting Pot
Ingeniería
- Rights
- embargoedAccess
- License
- Attribution-NonCommercial 4.0 International
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Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems |
| title |
Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems |
| spellingShingle |
Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems Communication Cooperation Artificial intelligence Large language models Melting Pot Ingeniería |
| title_short |
Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems |
| title_full |
Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems |
| title_fullStr |
Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems |
| title_full_unstemmed |
Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems |
| title_sort |
Enhancing multi-agent cooperation: the implementation and impact of a communication module in AI systems |
| dc.creator.fl_str_mv |
Ortiz Almanza, David Santiago |
| dc.contributor.advisor.none.fl_str_mv |
Manrique Piramanrique, Rubén Francisco |
| dc.contributor.author.none.fl_str_mv |
Ortiz Almanza, David Santiago |
| dc.subject.keyword.eng.fl_str_mv |
Communication Cooperation Artificial intelligence Large language models |
| topic |
Communication Cooperation Artificial intelligence Large language models Melting Pot Ingeniería |
| dc.subject.keyword.none.fl_str_mv |
Melting Pot |
| dc.subject.themes.spa.fl_str_mv |
Ingeniería |
| description |
As artificial intelligence increasingly permeates everyday life, the development of Large Language Models (LLMs) capable of effectively simulating complex social interactions and fostering cooperative behavior has become paramount. This paper explores the enhancement of cooperative capabilities in LLM-augmented Autonomous Agents (LAAs) through the integration of a dedicated communication module. Initial findings indicate that this module significantly enhances collaborative outcomes by enabling agents to share observations and insights, thereby fostering a more comprehensive understanding of their environment. This enhanced understanding has resulted in a 45% increase in per capita reward. Moreover, improved communication has facilitated more sustainable resource management and refined behavioral predictions among agents, leading to more strategic planning in multi-agent systems. Furthermore, the establishment of consensus through communication has proven invaluable in coordinating actions and promoting increased cooperation. However, the research also uncovers that while inter-agent communication can augment cooperation, it introduces risks of bias and misinformation. |
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2024 |
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2024-07-05T13:16:15Z |
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2024-07-04 |
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2024-07-04 |
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2025-05-30 |
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Trabajo de grado - Pregrado |
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info:eu-repo/semantics/bachelorThesis |
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Text |
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https://hdl.handle.net/1992/74464 |
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instname:Universidad de los Andes |
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reponame:Repositorio Institucional Séneca |
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eng |
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eng |
| dc.relation.references.none.fl_str_mv |
Press, O.U.: Cooperation. https://www.oed.com/search/dictionary/?scope=Entries&q=cooperation. Oxford English Dictionary, accessed: 15/02/2024 (2023) Dafoe, A., Hughes, E., Bachrach, Y., Collins, T., McKee, K.R., Leibo, J.Z., Larson, K., Graepel, T.: Open Problems in Cooperative AI (2020) Yousri, R., Essam, Z., Kareem, Y., Sherief, Y., Gamil, S., Safwat, S.: Illusionx: An llm-powered mixed reality personal companion (2024) https://doi.org/10.36227/techrxiv.170775603.33253596/v1 Agapiou, J.P., Vezhnevets, A.S., Du´e˜nez-Guzm´an, E.A., Matyas, J., Mao, Y., Sunehag, P., K¨oster, R., Madhushani, U., Kopparapu, K., Comanescu, R., Strouse, D., Johanson, M.B., Singh, S., Haas, J., Mordatch, I., Mobbs, D., Leibo, J.Z.: Melting Pot 2.0 (2023) Mosquera, M., Pinzon, J.S., Rios, M., Fonseca, Y., Giraldo, L.F., Quijano, N., Manrique, R.: Can LLM-Augmented autonomous agents cooperate?, An evaluation of their cooperative capabilities through Melting Pot (2024) Park, J.S., O’Brien, J.C., Cai, C.J., Morris, M.R., Liang, P., Bernstein, M.S.: Generative Agents: Interactive Simulacra of Human Behavior (2023) Qian, C., Liu, W., Liu, H., Chen, N., Dang, Y., Li, J., Yang, C., Chen, W., Su, Y., Cong, X., Xu, J., Li, D., Liu, Z., Sun, M.: ChatDev: Communicative Agents for Software Development (2024) Rasal, S.: LLM Harmony: Multi-Agent Communication for Problem Solving (2024) Leibo, J.Z., nez-Guzm´an, E.D., Vezhnevets, A.S., Agapiou, J.P., Sunehag, P., Koster, R., Matyas, J., Beattie, C., Mordatch, I., Graepel, T.: Scalable evaluation of multi-agent reinforcement learning with melting pot. (2021). https://doi.org/10.48550/arXiv.2107.06857 . PMLR. https://doi.org/10.48550/arXiv.2107.06857 Pinzón Roncancio, J.S.: Large language models como planeadores multiagente en entornos sociales. Technical report, Universidad de los Andes (2024). https://hdl.handle.net/1992/73756 GoOpenAI: ChromaDB: An Open Source Vector Database. Blog Post. Image inspired by content available at https://blog.gopenai.com/chromadb-an-open-source-vector-database-f1871580b412 (2023). |
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Attribution-NonCommercial 4.0 International |
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41 páginas |
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Universidad de los Andes |
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Ingeniería de Sistemas y Computación |
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Facultad de Ingeniería |
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Departamento de Ingeniería de Sistemas y Computación |
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Universidad de los Andes |
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Universidad de los Andes |
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Manrique Piramanrique, Rubén Franciscovirtual::18603-1Ortiz Almanza, David Santiago2024-07-05T13:16:15Z2025-05-302024-07-042024-07-04https://hdl.handle.net/1992/74464instname:Universidad de los Andesreponame:Repositorio Institucional Sénecarepourl:https://repositorio.uniandes.edu.co/As artificial intelligence increasingly permeates everyday life, the development of Large Language Models (LLMs) capable of effectively simulating complex social interactions and fostering cooperative behavior has become paramount. This paper explores the enhancement of cooperative capabilities in LLM-augmented Autonomous Agents (LAAs) through the integration of a dedicated communication module. Initial findings indicate that this module significantly enhances collaborative outcomes by enabling agents to share observations and insights, thereby fostering a more comprehensive understanding of their environment. This enhanced understanding has resulted in a 45% increase in per capita reward. Moreover, improved communication has facilitated more sustainable resource management and refined behavioral predictions among agents, leading to more strategic planning in multi-agent systems. Furthermore, the establishment of consensus through communication has proven invaluable in coordinating actions and promoting increased cooperation. However, the research also uncovers that while inter-agent communication can augment cooperation, it introduces risks of bias and misinformation.Pregrado41 páginasapplication/pdfengUniversidad de los AndesIngeniería de Sistemas y ComputaciónFacultad de IngenieríaDepartamento de Ingeniería de Sistemas y ComputaciónAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/embargoedAccesshttp://purl.org/coar/access_right/c_f1cfEnhancing multi-agent cooperation: the implementation and impact of a communication module in AI systemsTrabajo de grado - Pregradoinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_7a1fTexthttp://purl.org/redcol/resource_type/TPCommunicationCooperationArtificial intelligenceLarge language modelsMelting PotIngenieríaPress, O.U.: Cooperation. https://www.oed.com/search/dictionary/?scope=Entries&q=cooperation. Oxford English Dictionary, accessed: 15/02/2024 (2023)Dafoe, A., Hughes, E., Bachrach, Y., Collins, T., McKee, K.R., Leibo, J.Z., Larson, K., Graepel, T.: Open Problems in Cooperative AI (2020)Yousri, R., Essam, Z., Kareem, Y., Sherief, Y., Gamil, S., Safwat, S.: Illusionx: An llm-powered mixed reality personal companion (2024) https://doi.org/10.36227/techrxiv.170775603.33253596/v1Agapiou, J.P., Vezhnevets, A.S., Du´e˜nez-Guzm´an, E.A., Matyas, J., Mao, Y., Sunehag, P., K¨oster, R., Madhushani, U., Kopparapu, K., Comanescu, R., Strouse, D., Johanson, M.B., Singh, S., Haas, J., Mordatch, I., Mobbs, D., Leibo, J.Z.: Melting Pot 2.0 (2023)Mosquera, M., Pinzon, J.S., Rios, M., Fonseca, Y., Giraldo, L.F., Quijano, N., Manrique, R.: Can LLM-Augmented autonomous agents cooperate?, An evaluation of their cooperative capabilities through Melting Pot (2024)Park, J.S., O’Brien, J.C., Cai, C.J., Morris, M.R., Liang, P., Bernstein, M.S.: Generative Agents: Interactive Simulacra of Human Behavior (2023)Qian, C., Liu, W., Liu, H., Chen, N., Dang, Y., Li, J., Yang, C., Chen, W., Su, Y., Cong, X., Xu, J., Li, D., Liu, Z., Sun, M.: ChatDev: Communicative Agents for Software Development (2024)Rasal, S.: LLM Harmony: Multi-Agent Communication for Problem Solving (2024)Leibo, J.Z., nez-Guzm´an, E.D., Vezhnevets, A.S., Agapiou, J.P., Sunehag, P., Koster, R., Matyas, J., Beattie, C., Mordatch, I., Graepel, T.: Scalable evaluation of multi-agent reinforcement learning with melting pot. (2021). https://doi.org/10.48550/arXiv.2107.06857 . PMLR. https://doi.org/10.48550/arXiv.2107.06857Pinzón Roncancio, J.S.: Large language models como planeadores multiagente en entornos sociales. Technical report, Universidad de los Andes (2024). https://hdl.handle.net/1992/73756GoOpenAI: ChromaDB: An Open Source Vector Database. Blog Post. Image inspired by content available at https://blog.gopenai.com/chromadb-an-open-source-vector-database-f1871580b412 (2023).201913600Publication9f6e12e0-098e-4548-ab81-75552e8385e7virtual::18603-19f6e12e0-098e-4548-ab81-75552e8385e7virtual::18603-1ORIGINALEnhancing_Multi_Agent_Cooperation__The_Implementation_and_Impact_of_a_Communication_Module_in_AI_Systems.pdfEnhancing_Multi_Agent_Cooperation__The_Implementation_and_Impact_of_a_Communication_Module_in_AI_Systems.pdfRestricción de acceso hasta mayo del 2025. 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