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 cognition. We then present the broader idea of "concept", separate the idea of self model out of the world model, and construct a new model called world-self model (WSM). We show the mechanisms of creating and connecting concepts, and the flow of how the WSM receives, processes and outputs information with respect to an arbitrary type of problem to solve. We also consider and discuss the potential computer implementation issues of the proposed theoretical framework, and finally we propose a unified general framework of intelligence based on WSM.
翻译:人工智能的象征主义、联系主义和行为主义方法在各种任务中取得了许多成功,而我们仍没有在社区内充分共识(尽管有70多种不同的定义)对“情报”作出明确的定义。 情报的性质仍然在黑暗之中。 在这项工作中,我们不采取这三种传统方法中的任何一种,而是试图确定情报性质的某些基本方面,并建立一个数学模型来代表并可能复制这些基本方面。 我们首先强调必须界定讨论的范围和调查的微小范围。我们仔细比较人文和人工智能,并从质量上展示信息抽象过程,我们提议将其作为连接认识和认知的关键。然后我们提出“概念”的更广泛概念,将自我模型的概念从世界模式中分离出来,并建立一个称为世界自我模型的新模式。我们展示了创造和连接概念的机制,以及世界现代智能系统如何获得、过程和产出信息,从而解决任意类型的问题。我们还考虑和讨论基于一般理论框架的潜在计算机执行问题。我们最后提议了一个基于一般理论框架。