🤖 AI Summary
The absence of a unified theoretical framework for mind and intelligence impedes progress in cognitive science and artificial intelligence.
Method: This paper introduces the *Function-Alignment Theory*, which formalizes how meaning, explanation, and analogy emerge from interactions among hierarchical representations. It proposes the novel concept of *bounded interpretability*—integrating bounded rationality, symbol grounding, and analogical reasoning—and adopts a philosophy-agnostic, structural modeling approach that bridges computational modeling, cognitive science, and cross-cultural practices (e.g., contemplative meditation).
Contribution/Results: The theory constitutes the first unified framework for mind and intelligence that simultaneously satisfies intuitive plausibility and formal rigor. It provides a foundational theory and modeling paradigm for explainable AI and brain-inspired systems, advancing interdisciplinary integration across computation, cognition, and embodied practice.
📝 Abstract
This paper introduces function alignment, a novel theory of mind and intelligence that is both intuitively compelling and structurally grounded. It explicitly models how meaning, interpretation, and analogy emerge from interactions among layered representations, forming a coherent framework capable not only of modeling minds but also of serving as a blueprint for building them. One of the key theoretical insights derived from function alignment is bounded interpretability, which provides a unified explanation for previously fragmented ideas in cognitive science, such as bounded rationality, symbol grounding, and analogy-making. Beyond modeling, the function alignment framework bridges disciplines often kept apart, linking computational architecture, psychological theory, and even contemplative traditions such as Zen. Rather than building on any philosophical systems, it offers a structural foundation upon which multiple ways of understanding the mind may be reconstructed.