Towards autonomous normative multi-agent systems for Human-AI software engineering teams
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
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| _version_ | 1866912742634422272 |
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| author | Dam, Hoa Khanh Mahala, Geeta Hoda, Rashina Zheng, Xi Conati, Cristina |
| author_facet | Dam, Hoa Khanh Mahala, Geeta Hoda, Rashina Zheng, Xi Conati, Cristina |
| contents | This paper envisions a transformative paradigm in software engineering, where Artificial Intelligence, embodied in fully autonomous agents, becomes the primary driver of the core software development activities. We introduce a new class of software engineering agents, empowered by Large Language Models and equipped with beliefs, desires, intentions, and memory to enable human-like reasoning. These agents collaborate with humans and other agents to design, implement, test, and deploy software systems with a level of speed, reliability, and adaptability far beyond the current software development processes. Their coordination and collaboration are governed by norms expressed as deontic modalities - commitments, obligations, prohibitions and permissions - that regulate interactions and ensure regulatory compliance. These innovations establish a scalable, transparent and trustworthy framework for future Human-AI software engineering teams. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_02329 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards autonomous normative multi-agent systems for Human-AI software engineering teams Dam, Hoa Khanh Mahala, Geeta Hoda, Rashina Zheng, Xi Conati, Cristina Software Engineering This paper envisions a transformative paradigm in software engineering, where Artificial Intelligence, embodied in fully autonomous agents, becomes the primary driver of the core software development activities. We introduce a new class of software engineering agents, empowered by Large Language Models and equipped with beliefs, desires, intentions, and memory to enable human-like reasoning. These agents collaborate with humans and other agents to design, implement, test, and deploy software systems with a level of speed, reliability, and adaptability far beyond the current software development processes. Their coordination and collaboration are governed by norms expressed as deontic modalities - commitments, obligations, prohibitions and permissions - that regulate interactions and ensure regulatory compliance. These innovations establish a scalable, transparent and trustworthy framework for future Human-AI software engineering teams. |
| title | Towards autonomous normative multi-agent systems for Human-AI software engineering teams |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2512.02329 |