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96 5 A Generic Architecture of Human-Like Cognition

data, rather than mainly embodying speculative notions; however, given the current state of knowledge, this could not be done to a complete extent, and there is still some speculation involved here and there.

While based on understandings of human intelligence, the integrative diagram is intended to serve as an architectural outline for human-like general intelligence more broadly. For example, CogPrime is explicitly not intended as a precise emulation of human intelligence, and does many things quite differently than the human mind, yet can still fairly straightforwardly be mapped into the integrative diagram.

The integrative diagram focuses on structure, but this should not be taken to represent a valuation of structure over dynamics in our approach to intelligence. Following chapters treat various dynamical phenomena in depth.

5.2 Key Ingredients of the Integrative Human-Like Cognitive Architecture Diagram

The main ingredients we've used in assembling the integrative diagram are as follows:

• Our own views on the various types of memory critical for human-like cognition, and the need for tight, "synergetic" interactions between the cognitive processes focused on these
• Aaron Sloman's high-level architecture diagram of human intelligence [Slo01], drawn from his CogAff architecture, which strikes me as a particularly clear embodiment of "modern common sense" regarding the overall architecture of the human mind. We have added only a couple items to Sloman's high-level diagram, which we felt deserved an explicit high-level role that he did not give them: emotion, language and reinforcement.
• The LIDA architecture diagram presented by Stan Franklin and Bernard Baars [BF09]. We think LIDA is an excellent model of working memory and what Sloman calls "reactive processes", with well-researched grounding in the psychology and neuroscience literature. We have adapted the LIDA diagram only very slightly for use here, changing some of the terminology on the arrows, and indicating where parts of the LIDA diagram indicate processes elaborated in more detail elsewhere in the integrative diagram.
• The architecture diagram of the Psi model of motivated cognition, presented by Joscha Bach in [Bac09] based on prior work by Dietrich Dorner [Dör02]. This diagram is presented without significant modification; however it should be noted that Bach and Dorner present this diagram in the context of larger and richer cognitive models, the other aspects of which are not all incorporated in the integrative diagram.
• James Albus's three-hierarchy model of intelligence [AM01], involving coupled perception, action and reinforcement hierarchies. Albus's model, utilized in the creation of intelligent unmanned automated vehicles, is a crisp embodiment of many ideas emergent from the field of intelligent control systems.
• Deep learning networks as a model of perception (and action and reinforcement learning), as embodied for example in the work of Itamar Arel [ARC09] and Jeff Hawkins [HB06]. The integrative diagram adopts this as the basic model of the perception and action subsystems of human intelligence. Language understanding and generation are also modeled according to this paradigm.

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