EVOLVABLE ARCHITECTURES FOR HUMAN-LIKE MINDS

Abstract

Introduction Our project combines empirical, philosophical and computational theories and approaches, aiming (eventually) to explain many human, animal and robot phenomena, e.g. varieties of motivation, emotions, perceptual functions, reasoning, learning, and varieties of consciousness. We regard intuitive concepts of mentality as "cluster" concepts referring to implicitly presupposed virtual machine (VM) architectures. These pre-theoretical architectures are very crude approximations to diverse actual VM architectures, which vary during development, across species, and after damage or disease. Many disagreements on topics like `emotion', `consciousness', `intentionality' arise because researchers focus on different sub-clusters of capabilities and mechanisms within such architectures. Researchers studying different aspects of mind are often unaware of what they are ignoring, like the proverbial blind men describing an elephant. Powerful theories require knowledge about evolut