Development of a Decision-Support System Based on Emergent Interaction

当考虑在大规模和复杂的系统中解决工程问题时，包含双向交互的紧急方法是重要的，这使我们能够以自适应或交互的方式提取决策模型。在本研究中，旨在设计一种方法，其中的建模过程中嵌入的解决方案的过程中，一个交互式的信息场以及紧急计算方法已被（重新）构建。要点如下。(1)突现计算方法的重构--基于强化和基于遗传的机器学习技术，设计了一种基于模拟的决策规则获取和调整方法。(2)设计并实现了一个交互式信息场（I）--一个明确考虑子模型间交互的层次自治分散框架，并研究了基于该框架的仿真决策模型原型。(3)基于Agent和接口协同进化的框架，设计并实现了一个交互式信息场（II）--一种决策和学习方法，并研究了基于该框架的学习Agent模型原型

When considering an engineering problem-solving in large-scaled and complicated systems, an emergent approach containing bi-directional interactions is important, which enables us to extract a decision-making model in an adaptive or an interactive manner. In this research, aiming at designing a methodology in which a modeling process is embedded in a solution process, an interactive information field as well as an emergent computing method have been (re)constructed. The key points are as follows.(1) Reconstruction of emergent computing method - a simulation-based method for acquiring and adjusting decision-making rules has been designed, based on both reinforcement and genetics-based machine learning techniques.(2) Design and implementation of an interactive information field (I) - an hierarchical autonomous decentralized framework in which an interaction among sub-models are explicitly considered has been designed, and an prototype of a simulation and decision-making model based on the framework has been investigated.(3) Design and implementation of an interactive information field (II) - a decision-making and learning method has been developed based on such framework where an agent and an interface are to be co-evolved, and an prototype of an learning agent model based on the framework has been investigated