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Rocking Stamper and Jumping Snakes from a Dynamical Systems Approach to Artificial Life

机译：从动力学系统到人工生命的摇摆压模和跳跃蛇

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Dynamical systems offer intriguing possibilities as a substrate for the generation of behavior because of their rich behavioral complexity. However this complexity together with the largely covert relation between the parameters and the behavior of the agent is also the main hindrance in the goal oriented design of a behavior system. This paper presents a general approach to the self-regulation of dynamical systems so that the design problem is circumvented. We consider the controller (a neural network) as the mediator for changes in the sensor values over time and define a dynamics for the parameters of the controller by maximizing the dynamical complexity of the sensorimotor loop under the condition that the consequences of the actions taken are still predictable. This very general principle is given a concrete mathematical formulation and is implemented in an extremely robust and versatile algorithm for the parameter dynamics of the controller. We consider two different applications, a mechanical device called the rocking stamper and the ODE simulations of a "snake" with five degrees of freedom. In these and many other examples studied we observed various behavior modes of high dynamical complexity.
机译：动力系统由于其丰富的行为复杂性，为产生行为提供了有趣的可能性。然而，这种复杂性以及参数与代理行为之间的隐秘关系也是行为系统面向目标设计的主要障碍。本文提出了一种动态系统自我调节的通用方法，从而规避了设计问题。我们将控制器（神经网络）视为传感器值随时间变化的媒介，并通过在发生动作后果的条件下最大化传感器运动回路的动态复杂度来定义控制器参数的动力学。仍然可以预测。这个非常通用的原理给出了具体的数学公式，并以极其健壮和通用的算法实现，用于控制器的参数动力学。我们考虑两种不同的应用，一种称为摇摆压模的机械设备，以及一种具有五个自由度的“蛇”的ODE模拟。在研究的这些和其他许多示例中，我们观察到了高动态复杂度的各种行为模式。

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