The Economic Foundation for Neural Computing Systems

这是一个探索性研究的小额赠款， 数学经济学的框架来模拟协调 处理大规模问题的多个计算单元 解决 作者正在开发一个详细的形式主义 一个大规模并行计算系统， 这是一个经济资源分配问题。 一 计算将被视为一个生产过程， 具体的输出，需要一定的投入。 正如生产 商品被组织成并行和串行阶段， 中间货物，计算问题将被组织成 具有中间输出的并行和串行步骤。 输入和 产出将被定价，利润将被定义为每个 计算单位 各单位出入境依据 rofitability可以解释为一种形式的适应性学习。 数学经济学将允许最优的 价格将有效地实现系统目标。 的 作者将研究的存在性，最优性和稳定性， 均衡价格和分配， 这种经济解决方案以及潜在的学习行为驱动 盈利能力。 该研究的意义在于它探讨了 经济科学和知识 从计算机科学可以整合产生新的知识。

This is a Small Grant for Exploratory Research which uses the framework of mathematical economics to model the coordination of amultitude of computational units engaged in large-scale problem solving. The authors are working on developing a detailed formalism of a massively parallel computing system that lends itself to a representation as an economic resource allocation problem. A computation will be regarded as a production process that yields a specific output and requires certain inputs. Just as production of commodities are organized into parallel and serial stages with intermediate goods, a computational problem will be organized into parallel and serial steps with intermediate outputs. Inputs and outputs will be priced, and profits will be defined for each computational unit. Entry and exit of individual units based on rofitability can be interpreted as a form of adaptive learning. Mathematical economic will allow the characterization of optimal prices that will achieve the system objective efficiently. The authors will study the existence, optimality, and stability of equilibrium prices and allocations, the practical implementation of this economic solution, and the potential learning behavior driven by profitability. The research is significant in that it explores the way in which knowledge from economic science and knowledge fromcomputer science can be integrated to produce new knowledge.