Logos introduces a new cognitive architecture that enhances reasoning and learning across various domains, indicating improved adaptability.
This paper introduces Logos, a cognitive architecture designed to unify reasoning and continual learning within a structured interaction loop. The architecture models problem-solving as a hypothesis-driven cognitive cycle, where reasoning, action, and learning are tightly coupled. A key feature of Logos is its explicit treatment of evaluation as a mechanism that connects outcomes to future behavior, enabling iterative adaptation and experience accumulation. We present the architectural framework, core design principles, and illustrative case studies demonstrating how the system operates across different domains.
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Seongyun Ko (2026) studied this question.
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