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Investigating the properties of bio-chemical networks of artificial organisms with opposing behaviours

机译:研究行为相反的人造生物的生化网络的性质

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Organisms, be it singled-celled organisms or multi-cellular organisms, are constantly faced with opposing objectives requiring different sets of behaviours. These behaviours can be classified into two, predatory behaviours or anti-prey behaviours, with one set of behaviours causing an opposite effect to the other. A healthy organism aims to achieve its equilibrium state or to be in homeostasis. Homeostasis is achieved when a balance between the two opposing behaviours is created and maintained. This raises some questions: is there an innate mechanism that encodes for these categories of behaviours? Is there also an innate mechanism(s) that resolves conflicts and allows switching between these two opposing behaviours? If we consider artificial organisms as single-celled organisms, how do the organisms' gene regulatory network, metabolic network and/or signalling network (their biochemical networks) maintain homeostasis of the organisms? This paper investigates the properties of the networks of best evolved artificial organisms, in order to help answer these questions, and guide the evolutionary development of controllers for artificial systems.
机译:生物,无论是单细胞生物还是多细胞生物,始终面临着需要不同行为的对立目标。这些行为可以分为两种,掠夺性行为或反捕食行为,其中一组行为与另一组行为产生相反的影响。健康的生物体旨在达到其平衡状态或处于体内平衡状态。当在两个相对行为之间建立并保持平衡时,就达到了稳态。这就提出了一些问题:是否存在一种固有机制可以对这些类别的行为进行编码?是否还有一个天生的机制可以解决冲突并允许在这两种相反的行为之间进行切换?如果我们将人工生物视为单细胞生物,那么生物的基因调控网络,代谢网络和/或信号网络(其生化网络)如何维持生物的体内平衡?本文研究了最佳进化人工生物网络的特性,以帮助回答这些问题,并指导人工系统控制器的进化发展。

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