4.4 Hybrid Cognitive Architectures 77
Monolithic:symbolic component "sits on top of" neural component and World < > Neural | a, = | Symbolic Hybrid:neural and symbolic components confront the world side by side a > Neural A World ¥ « » | Symbolic |
Tightly interactive hybrid:neural and symbolic components interact frequently, on the same time scale as their internal learning operations
Fig. 4.8: Broad categories of neural-symbolic architecture
Within the scope of hybrid neural-symbolic systems, there is another axis which Bader and Hitzler do not focus on, because the main interest of their review is in monolithic systems. We call this axis "interactivity"’, and what we are referring to is the frequency of high-information- content, high-influence interaction between the neural and symbolic components in the hybrid system. In a low-interaction hybrid system, the neural and symbolic components don’t exchange large amounts of mutually influential information all that frequently, and basically act like independent system components that do their learning/reasoning /thinking periodically sending each other their conclusions. In some cases, interaction may be asymmetric: one component may frequently send a lot of influential information to the other, but not vice versa. However, our hypothesis is that the most capable neural-symbolic systems are going to be the symmetrically highly interactive ones.
In a symmetric high-interaction hybrid neural-symbolic system, the neural and symbolic components exchange influential information sufficiently frequently that each one plays a major role in the other one’s learning /reasoning/thinking processes. Thus, the learning processes of each component must be considered as part of the overall dynamic of the hybrid system. The two components aren’t just feeding their outputs to each other as inputs, they’re mutually guiding each others’ internal processing.
One can make a speculative argument for the relevance of this kind of architecture to neuro- science. It seems plausible that this kind of neural-symbolic system roughly emulates the kind of interaction that exists between the brain’s neural subsystems implementing localist symbolic processing, and the brain’s neural subsystems implementing globalist, classically “connection- ist” processing. It seems most likely that, in the brain, symbolic functionality emerges from an underlying layer of neural dynamics. However, it is also reasonable to conjecture that this symbolic functionality is confined to a functionally distinct subsystem of the brain, which then
HOUSE_OVERSIGHT_012993