复杂景观中的进化搜索代理-能力和元能力作用的新模型（EVOLINO和其他模拟工具）
Evolutionary search agents in complex landscapes - a new model for the role of competence and meta-competence (EVOLINO and other simulation tools)
摘要：
获得胜任能力是在复杂和迅速变化的现代工作世界中坚持自己的能力的关键因素。本文从几何导向进化理论（GOE THE）的一般概念出发，考察了能力的进化，即能力在进化问题解决过程中的作用，以及作为元能力的灵活性的作用。我们使用进化搜索代理作为真实个人和群体的抽象模型。在第一种方法中，代理搜索更好的能力简档。在第二种方法中，他们使用能力来解决问题。搜索代理在一个抽象的价值景观，健身景观。进化搜索代理和其他代理模型之间的关键区别在于，新代理的交互模式包含进化搜索策略。一个特殊的仿真工具EVOLINO允许模拟搜索代理在复杂景观中的爬山过程。
英文摘要：
The acquisition of competence is a key element in the ability to assert oneself in the complex and rapidly changing modern worlds of work. This paper examines the evolution of competence, i.e. the role of competences in an evolutionary problem-solving process, and the role of flexibility as a meta-competence from the perspective of the general concept of Geometrically-Oriented Evolution THEory (G_O_E_THE). We use evolutionary search agents as abstract models of real individuals and groups. In a first approach the agents search for better competence profiles. In a second approach they use competences to solve problems. A search agent operates in an abstract value landscape, a fitness landscape. The crucial difference between the evolutionary search agents and other agent models is the fact that interaction patterns of the new agents incorporate evolutionary search strategies. A special simulation tool called EVOLINO allows to simulate the hill-climbing process of search agents in complex landscapes.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
