Niche construction emphasizes the active aspect of life forms that alter their environment via feedback loops in which that environment inevitably changes their behavior, structure, and future evolution. We argue that this powerful dynamic is general, extending far beyond typical applications in ecology and evolutionary biology. We explain how niche construction extends the scope of classical predictive and control loops beyond the nervous system and organism-level. Examples from cognitive science, psychopathology, cell and developmental biology, cancer biology, robotics, and AI illustrate how agents use living and non-living aspects of their microenvironment as a scratchpad, allowing active long-term memory that supports cohesion of agency over time. Niche construction enables "offloading" to the environment (externalizing) various cognitive operations, including planning, problem solving, and social coordination. We also discuss niche construction an example of the plasticity of the machine/data mapping, enabling analysis of systems from the perspective of the patterns within excitable media (agential data). Finally, we show wetlab data for a new kind of niche construction: active stigmergy, in which cells leave dynamic, bioelectrically-active components in the microenvironment. By recognizing niche construction in novel spaces, important invariants across disciplines can drive advances in biomedicine, engineering, and AI.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
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