Search Results for author:
Found 17 papers, 11 papers with code
Gradient-based Design of Computational Granular Crystals
There is growing interest in engineering unconventional computing devices that leverage the intrinsic dynamics of physical substrates to perform fast and energy-efficient computations.
Efficient automatic design of robots
Robots are notoriously difficult to design because of complex interdependencies between their physical structure, sensory and motor layouts, and behavior.
Universal Mechanical Polycomputation in Granular Matter
Mechanical computers, wherein information processing is a material property emerging from the interaction of components with the environment, are one such class of devices.
Selection for short-term empowerment accelerates the evolution of homeostatic neural cellular automata
Empowerment -- a domain independent, information-theoretic metric -- has previously been shown to assist in the evolutionary search for neural cellular automata (NCA) capable of homeostasis when employed as a fitness function.
Empowered Neural Cellular Automata
Information-theoretic fitness functions are becoming increasingly popular to produce generally useful, task-independent behaviors.
Evolving Programmable Computational Metamaterials
Granular metamaterials are a promising choice for the realization of mechanical computing devices.
Selecting Continuous Life-Like Cellular Automata for Halting Unpredictability: Evolving for Abiogenesis
Substantial efforts have been applied to engineer CA with desired emergent properties, such as supporting gliders.
A good body is all you need: avoiding catastrophic interference via agent architecture search
Efforts to combat catastrophic interference to date focus on novel neural architectures or training methods, with a recent emphasis on policies with good initial settings that facilitate training in new environments.
Scale invariant robot behavior with fractals
Finally, we show that biobots can spontaneously exhibit self similar attachment geometries, thereby suggesting that self similar behavior via self similar structure may be realizable across a wide range of robot platforms in future.
Scalable sim-to-real transfer of soft robot designs
The manual design of soft robots and their controllers is notoriously challenging, but it could be augmented---or, in some cases, entirely replaced---by automated design tools.
Embodiment dictates learnability in neural controllers
Catastrophic forgetting continues to severely restrict the learnability of controllers suitable for multiple task environments.
Word2vec to behavior: morphology facilitates the grounding of language in machines
Enabling machines to respond appropriately to natural language commands could greatly expand the number of people to whom they could be of service.
Automated shapeshifting for function recovery in damaged robots
We found that, especially in the case of "deep insult", such as removal of all four of the robot's legs, the damaged machine evolves shape changes that not only recover the original level of function (locomotion) as before, but can in fact surpass the original level of performance (speed).
Morphology dictates a robot's ability to ground crowd-proposed language
In this paper, we define a safe robot as one that receives a natural-language command from humans, considers an action in response to that command, and accurately predicts how humans will judge that action if is executed in reality.
How morphological development can guide evolution
Here, we report on a previously unknown phenomenon when embodied agents are allowed to develop and evolve: Evolution discovers body plans robust to control changes, these body plans become genetically assimilated, yet controllers for these agents are not assimilated.
Evolving soft locomotion in aquatic and terrestrial environments: effects of material properties and environmental transitions
Designing soft robots poses considerable challenges: automated design approaches may be particularly appealing in this field, as they promise to optimize complex multi-material machines with very little or no human intervention.
Scalable Co-Optimization of Morphology and Control in Embodied Machines
In psychology, the theory of embodied cognition posits that behavior arises from a close coupling between body plan and sensorimotor control, which suggests why co-optimizing these two subsystems is so difficult: most evolutionary changes to morphology tend to adversely impact sensorimotor control, leading to an overall decrease in behavioral performance.
