Introducing COGENT3: An AI Architecture for Emergent Cognition
This addresses the need for more adaptable AI systems in cognitive science and machine learning, though it appears incremental as it builds on existing concepts like pattern formation and group dynamics.
The paper tackles the problem of rigid AI architectures by introducing COGENT3, a system that enables emergent cognition through dynamic agent interactions, resulting in a more flexible and adaptive framework that mimics human cognitive processes.
This paper presents COGENT3 (or Collective Growth and Entropy-modulated Triads System), a novel approach for emergent cognition integrating pattern formation networks with group influence dynamics. Contrasting with traditional strategies that rely on predetermined architectures, computational structures emerge dynamically in our framework through agent interactions. This enables a more flexible and adaptive system exhibiting characteristics reminiscent of human cognitive processes. The incorporation of temperature modulation and memory effects in COGENT3 closely integrates statistical mechanics, machine learning, and cognitive science.