58 4 Brief Survey of Cognitive Architectures
CogPrime represents a significantly more effective approach to embodied human-like general intelligence. In our treatment of emergentist architectures, we pay particular attention to devel- opmental robotics architectures, which share considerably with CogPrime in terms of underlying philosophy, but differ via not integrating a symbolic “language and inference” component such as CogPrime includes.
In brief, we believe that the hybrid approach is the most pragmatic one given the current state of AI technology, but that the emergentist approach gets something fundamentally right, by focusing on the emergence of complex dynamics and structures from the interactions of simple components. So CogPrime is a hybrid architecture which (according to the cognitive synergy principle) binds its components together very tightly dynamically, allowing the emergence of complex dynamics and structures in the integrated system. Most other hybrid architectures are less tightly coupled and hence seem ill-suited to give rise to the needed emergent complexity. The other hybrid architectures that do possess the needed tight coupling, such as MicroPsi [Bac09], strike us as underdeveloped and founded on insufficiently powerful learning algorithms.
Cognitive architectures
Memory
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Fig. 4.1: Duch’s simplified taxonomy of cognitive architectures. CogPrime falls into the “hy- brid” category, but differs from other hybrid architectures in its focus on synergetic interactions between components and their potential to give rise to appropriate system-wide emergent struc- tures enabling general intelligence.
4.2 Symbolic Cognitive Architectures
A venerable tradition in AI focuses on the physical symbol system hypothesis [New90], which states that minds exist mainly to manipulate symbols that represent aspects of the world or themselves. A physical symbol system has the ability to input, output, store and alter symbolic entities, and to execute appropriate actions in order to reach its goals. Generally, symbolic cognitive architectures focus on “working memory” that draws on long-term memory as needed, and utilize a centralized control over perception, cognition and action. Although in principle such architectures could be arbitrarily capable (since symbolic systems have universal repre-
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