Paper page - Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Source: https://huggingface.co/papers/2504.01990

Abstract

This survey covers the design, evaluation, and improvement of intelligent agents based on modular, brain-inspired architectures, focusing on self-enhancement, multi-agent collaboration, and safety in AI systems.

The advent oflarge language models(LLMs) has catalyzed a transformative shift in artificial intelligence, paving the way for advanced intelligent agents capable of sophisticated reasoning, robust perception, and versatile action across diverse domains. As these agents increasingly drive AI research and practical applications, their design, evaluation, and continuous improvement present intricate, multifaceted challenges. This survey provides a comprehensive overview, framingintelligent agentswithin a modular,brain-inspiredarchitecture that integrates principles fromcognitive science,neuroscience, andcomputational research. We structure our exploration into four interconnected parts. First, we delve into the modular foundation ofintelligent agents, systematically mapping their cognitive, perceptual, andoperational modulesonto analogous human brain functionalities, and elucidating core components such asmemory,world modeling,reward processing, andemotion-like systems. Second, we discussself-enhancementand adaptive evolution mechanisms, exploring how agents autonomously refine their capabilities, adapt to dynamic environments, and achievecontinual learningthroughautomated optimizationparadigms, including emergingAutoMLandLLM-driven optimizationstrategies. Third, we examine collaborative and evolutionary multi-agent systems, investigating thecollective intelligenceemerging from agent interactions, cooperation, and societal structures, highlighting parallels to humansocial dynamics. Finally, we address the critical imperative of building safe, secure, andbeneficial AIsystems, emphasizing intrinsic and extrinsic security threats,ethical alignment,robustness, and practical mitigation strategies necessary for trustworthy real-world deployment.

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