Distinction and Play: Cognitive Boundaries of Knowledge

This paper explores the role of distinction in cognitive processes and its relationship with the phenomenon of Play. It examines the mechanisms of distinction in neural network models and introduces the concept of metagame as a means of transcending fixed boundaries. The study also considers the implications of artificial intelligence (AI) systems becoming aware of their own distinctions. It is hypothesized that the ability to revise distinctions may serve as a criterion for cognitive autonomy and a key factor in determining the limits of AI adaptability. Real-world examples from AI systems, philosophy, and game theory are introduced to illustrate how distinction operates in various domains. The framework of universal intelligence, as proposed by Legg and Hutter, is analyzed to contrast conventional AI adaptability with the capacity for self-revision of distinctions. Additional insights from machine learning research, particularly meta-learning and transfer learning, are incorporated to reinforce the argument.<br>