Artificial intelligence and large language models (LLMs) are reshaping scientific research by enabling autonomous research assistants that can perform complex tasks such as literature review, hypothesis generation, and experimental design. A key emerging approach is the use of multi-agent systems, where specialised AI agents collaborate to achieve research goals. Multi-agent
Research agents and tools represent a burgeoning field within artificial intelligence, where autonomous systems leverage large language models (LLMs) and modular architectures to facilitate scientific inquiry and innovation. These agents operate by integrating perception, reasoning, planning, and action capabilities, enabling them to perform tasks such as literature review, hypothesis generation,
Artificial intelligence (AI) agents are broadly defined as computational entities that perceive their environment and act autonomously to achieve specific goals (Russell & Norvig 2020). Foundational work in the field, dating back to its early formalisation, characterises intelligent agents by key properties such as autonomy, reactivity, proactiveness, and social ability,
A paradigm shift is taking place in the field of artificial intelligence (AI), moving from generative models that create synthetic content towards autonomous AI agents. These agents are capable of realising complex, open-ended goals with minimal human intervention (Kolt 2025). An AI agent is fundamentally a computational entity that uses
