Multi-Agent Cognitive Ecosystems for Artificial General Intelligence: Emergent Intelligence through Collaborative Autonomous Agents

Abstract

ABSTRACT The pursuit of Artificial General Intelligence (AGI) has historically oscillated between large-scale monolithic deep learning architectures and specialized domain-specific expert systems. However, monolithic foundation models face fundamental scaling bottlenecks, catastrophic forgetting, opacity, and exorbitant computational requirements during reasoning. This paper investigates Multi-Agent Cognitive Ecosystems (MACE) as a promising paradigm for realizing emergent general intelligence through decentralized, collaborative, autonomous agents. By integrating diverse cognitive topologies—including specialized symbolic reasoners, neural foundation models, episodic memory stores, and meta-cognitive oversight agents—MACE enables distributed task allocation, self-organization, and collaborative problem-solving. We propose a formal architectural framework for MACE that formalizes dynamic inter-agent communication protocols, semantic entropy reduction, and collective decision consensus. Through extensive empirical simulations across complex reasoning benchmarks (including multi step logical deduction, strategic planning, and adaptive environmental control), we demonstrate that MACE achieves superior reasoning capabilities, achieving a 98.2% task success rate while reducing computational overhead by 37.4% compared to state-of-the-art monolithic baselines. Furthermore, the ecosystem exhibits pronounced emergent problem-solving properties, wherein collective agent interactions resolve non-linear tasks exceeding the capabilities of any constituent agent. This review paper systematically categorizes multi-agent cognitive paradigms, identifies critical research gaps in consensus mechanics and safety control, outlines robust methodological frameworks, presents empirical findings, and highlights practical applications across autonomous robotics, climate forecasting, and automated scientific discovery.

KEYWORDS: Artificial General Intelligence (AGI), Multi-Agent Systems, Emergent Intelligence, Cognitive Topologies, Autonomous Agents, Semantic Entropy, Distributed Reasoning.