A World-Self Model Towards Understanding Intelligence
Yutao Yue

TL;DR
This paper introduces a novel mathematical model called the world-self model (WSM) to better understand the fundamental aspects of intelligence, emphasizing the connection between perception and cognition through information abstraction.
Contribution
It proposes a new theoretical framework for intelligence based on the separation of self and world models, advancing understanding beyond traditional AI approaches.
Findings
Qualitative demonstration of information abstraction as key to perception and cognition
Construction of the world-self model (WSM) for representing intelligence
Discussion of potential implementation issues and a unified framework for intelligence
Abstract
The symbolism, connectionism and behaviorism approaches of artificial intelligence have achieved a lot of successes in various tasks, while we still do not have a clear definition of "intelligence" with enough consensus in the community (although there are over 70 different "versions" of definitions). The nature of intelligence is still in darkness. In this work we do not take any of these three traditional approaches, instead we try to identify certain fundamental aspects of the nature of intelligence, and construct a mathematical model to represent and potentially reproduce these fundamental aspects. We first stress the importance of defining the scope of discussion and granularity of investigation. We carefully compare human and artificial intelligence, and qualitatively demonstrate an information abstraction process, which we propose to be the key to connect perception and…
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