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THE INFORMATION REQUIREMENTS OF COMPLEX BIOLOGICAL AND ECONOMIC SYSTEMS WITH ALGORITHMIC INFORMATION THEORY

机译:具有算法论的复杂生物经济系统信息需求

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This article interprets the natural laws creating and maintaining a complex system, such as an ecology or an economy, distant from equilibrium, as computations on a real world Universal Turing Machine (UTM). As a laboratory, UTM can simulate the real world UTM, from the perspective of algorithmic information theory, the number of bits in the shortest, appropriately coded binary algorithm that specifies a real world system on a laboratory UTM defines its algorithmic entropy and its information content. As only algorithmic entropy differences matter, and differences are UTM-independent, differences measured on the laboratory UTM align with entropy changes in the real world. The system's distance from equilibrium in bits defines its order. Computations require energy. Landauer's principle identifies the minimum energy per bit (or the real world equivalent) to drive the computation that creates and sustains a real world system in a homeostatic state distant from equilibrium. This high-grade energy carries the computational instructions that do work on the system, ejecting disorder as heat and waste. While replication algorithms drive the emergence of complex ecological systems (doi:10.1016/j.biosystems.2015.11.008), in economic systems, individual agent behaviour can be captured by computer algorithms akin to the perspective of an adaptive system paradigm. Rather than specifying detailed behavioural routines for an economy, a narrative is used to identify the information drivers that create an ordered far-from-equilibrium economic system. The narrative shows that, somewhat like the interdependence of species in a vibrant ecology, agents trade, utilise technology, and amalgamate to form more complex structures creating order and driving the economy further from equilibrium. An ordered economy is a better economy. Order-creating investments (infrastructure, machines etc.) enhance economic performance, in contrast to non-ordering investments that extract wealth from others, adding nothing.
机译:本文将创建和维护远离平衡的复杂系统(例如生态系统或经济系统)的自然法则解释为在真实世界通用图灵机(UTM)上的计算。作为实验室,UTM可以从算法信息论的角度模拟真实世界的UTM,在指定实验室UTM上的真实系统的最短,经过适当编码的二进制算法中,其位数定义了其算法熵和信息内容。由于仅算法上的熵差异很重要,并且差异与UTM无关,因此在实验室UTM上测得的差异与现实世界中的熵变化一致。系统到平衡的距离(以位为单位)定义了其顺序。计算需要能量。 Landauer原理确定了每位最小能量(或等效于现实世界的能量),以驱动计算,该计算在远离平衡的稳态状态下创建并维持现实世界的系统。这种高等级的能量带有在系统上起作用的计算指令,会以热量和废物的形式散乱。尽管复制算法推动了复杂生态系统的出现(doi:10.1016 / j.biosystems.2015.11.008),但在经济系统中,可以通过计算机算法捕获个体代理的行为,类似于自适应系统范式的观点。叙事不是指定经济体的详细行为常规,而是用于识别创建有序的,远离均衡的经济系统的信息动因。叙述表明,就像某种物种在充满生机的生态系统中的相互依存关系一样,代理商进行交易,利用技术和合并形成更复杂的结构,从而创造秩序并推动经济进一步远离均衡。有序经济是更好的经济。创造订单的投资(基础设施,机器等)可以提高经济绩效,而非订购投资则可以从他人身上获取财富,却一无所获。

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