Two recent papers explore the development and application of agent-based economic models. The first paper, "From Economic Agents to Agentic Economies," outlines a blueprint for building sophisticated economic world models that simulate heterogeneous agents interacting within evolving markets and institutions. It identifies a gap in current research, which is largely concentrated on simpler agent environments, and calls for more advanced systems with self-evolving agents and empirical alignment. The second paper, "Dr. AGENTONOMICS," details a didactic experiment applying the AGENTONOMICS framework, which treats AI agents as economic entities. This framework is used to create a lecture agent that tutors students on AGENTONOMICS concepts and has the potential to evolve into a multimodal instructor, design consultant, and meta-agent for AI development. AI
IMPACT These papers propose advanced frameworks for simulating economies with AI agents, potentially accelerating AI training and evaluation in economic contexts.
RANK_REASON The cluster consists of two academic papers published on arXiv, detailing research into agent-based economic models and AI agent frameworks.
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- ADMRF
- AGENTONOMICS
- AGENTONOMICS Design & Management Reference Framework
- AI agents
- Dr. AGENTONOMICS
- Technical University of Munich
- alphaXiv
- arXiv
- arXivLabs
- CatalyzeX
- Connected Papers
- CORE Recommender
- DagsHub
- Economic World Models
- Gotit.pub
- Hugging Face
- Influence Flower
- Litmaps
- ScienceCast
- scite Smart Citations
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