John Rieffel

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Emergent Geometric Organization and Informative Dimensions in Coevolutionary Algorithms A dissertation presented to the Faculty of the Graduate School of Arts and Sciences of Brandeis University, Waltham, Massachusetts by Anthony Bucci Coevolutionary algorithms vary entities which can play two or more distinct, interacting roles, with the hope of producing(More)
With recent advances in materials, interest is being applied to the idea of robots with few if any rigid parts, able to substantially deform themselves in order to flow around, and even through objects. In order to accomplish these goals in an efficient and affordable manner, space and power will be at a premium, and so soft robots will most likely be both(More)
Many of the most profound works of artificial life have emerged through the composition of physical simulation and generative representations. And yet, while physics engines are becoming more realistic, and generative representations are growing more powerful, they are still predominantly used to simulate rigid objects. The natural world and its organisms(More)
Traditional engineering approaches strive to avoid, or actively suppress, nonlinear dynamic coupling among components. Biological systems, in contrast, are often rife with these dynamics. Could there be, in some cases, a benefit to high degrees of dynamical coupling? Here we present a distributed robotic control scheme inspired by the biological phenomenon(More)
Few evolved designs are subsequently manufactured into physical objects – the vast majority remain on the virtual drawing board. We suggest two sources of this “Fabrication Gap”. First, by being descriptive rather than prescriptive, evolutionary design runs the risk of evolving interesting yet unbuildable objects. Secondly, in a wide range of interesting(More)
Evolutionary designs based upon Artificial Ontogenies are beginning to cross from virtual to real environments. In such systems the evolved genotype is an indirect, procedural representation of the final structure. To date, most Artificial Ontogenies have relied upon an error-free development process to generate their phenotypic structure. In this paper we(More)
Given the complexity of the problem, genetic algorithms are one of the more promising methods of discovering control schemes for soft robotics. Since physically embodied evolution is time consuming and expensive, an outstanding challenge lies in developing fast and suitably realistic simulations in which to evolve soft robot gaits. We describe two parallel(More)
Completely soft and flexible robots offer to revolutionize fields ranging from search and rescue to endoscopic surgery. One of the outstanding challenges in this burgeoning field is the chicken-and-egg problem of body-brain design: Development of locomotion requires the preexistence of a locomotion-capable body, and development of a location-capable body(More)