Artificial Ontogenies, which are inspired by biological development, have been used to automatically generate a wide array of novel objects, some of which have recently been manufactured in the real world. The majority of these evolved designs have been evaluated in simulation as completed objects, with no attention paid to how, or even if, they can be realistically built. As a consequence, significant human effort is required to transfer the designs to the real world. One way to reduce human involvement in this regard is to evolve how to build rather than what to build, by using prescriptive rather than descriptive representations. In the context of Artificial Ontogenies, this requires what we call Situated Development, in which an object’s development occurs in the same environment as its final evaluation. Not only does this produce sufficient information on how to build evolved designs, but it also ensures that only buildable designs are evolved. In this paper we explore the consequences of Situated Development, and demonstrate how it can be incorporated into Artificial Ontogenies in order to generate buildable objects, which can be sequentially assembled in a realistic 3-D physics environment.

We describe a new general algorithm for the automated design, analysis and repair of nonlinear physical systems. The process iterates a two-phase exploration-estimation cycle. The exploratory phase seeks a new improvement or test to perform to the system based on some initial internal model. The estimation phase performs the suggested operation and observes the outcomes; it then improves the internal model so as to explain all observations so far. This process relies on very few, targeted, and carefully planned interactions with the physical systems. We describe an implementation of this method using two evolutionary algorithms, where the exploratory phase uses a simulator to evolve improvements or tests, and the estimation phase uses observations to evolve the simulator itself. We demonstrate this algorithm for analysis, design and repair of electromechanical systems.

Abstract. This talk will outline challenges and opportunities in translating evolutionary

Can a computer ultimately augment or replace human invention?

Evolutionary Design has been used to automatically generate a wide variety of novel and creative objects such as circuits, robots, and satellite antennae. And yet, despite the availability of sophisticated rapid prototyping machines capable of printing objects out of plastic, metal, and even circuitry, relatively few of these evolved designs have been physically manufactured in the real world. We argue