Random Boolean networks have been used widely to explore aspects of gene regulatory networks. A modified form of the model through which to systematically explore the effects of increasing the number of gene states has previously been introduced. In this paper, these discrete dynamical networks are coevolved within coupled, rugged fitness landscapes to explore their behaviour. Results suggest the general properties of the Boolean model remain with higher valued logic regardless of the update scheme or fitness sampling method. Introducing topological asymmetry in the coevolving networks is seen to alter behaviour.

翻译：随机布尔网络已被广泛用于探索基因调控网络的特性。先前已引入一种模型修正形式，通过该形式可系统研究增加基因状态数量的影响。本文中，这些离散动力网络在耦合的崎岖适应度景观内进行协同演化，以探究其行为。结果表明，无论采用何种更新方案或适应度采样方法，布尔模型的一般性质在多值逻辑中保持不变。引入协同演化网络中的拓扑不对称性会改变其行为。