A symbolic/subsymbolic interface protocol for cognitive modeling

作者：Simen Patrick^*; Polk Thad

来源：Logic Journal of the IGPL, 2010, 18(5): 705-761.

DOI：10.1093/jigpal/jzp046

• problem solving
• production system
• neural network
• diffusion
• decision making
• symbolic
• subsymbolic

Researchers studying complex cognition have grown increasingly interested ill napping symbolic cognitive architectures onto subsymbolic brain models. Such a mapping seems essential for understanding cognition under all but the most extreme viewpoints (namely, that cognition consists exclusively of digitally implemented rules; or instead, involves no rules whatsoever). Making this mapping reduces to specifying an interlace between symbolic and subsymbolic descriptions or brain activity. To that end, we propose parameterization techniques for building cognitive models a programmable, structured, recurrent neural networks. Feedback strength in these models determines whether their components implement, classically subsymbolic neural network functions (e.g., pattern recognition), or instead, logical rules and digital memory. These techniques support, the implementation of limited production systems. Though inherently sequential and symbolic, these neural production systems can exploit principles of parallel, analog processing from decision-making models in psychology and neuroscience to explain the effects of brain damage on problem solving behavior.

• 出版日期2010-10