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08 Jul 2018
Dario Floreano Plenary Talk at WCCI 2018
Abstract: Evolutionary computation has been successfully used for understanding the emergence of a wide range of biological intelligent behaviors for which there is no fossil record, such as altruism, division of labor, communication, non-deterministic behavior, and reward-based learning. These methods have also been used for generating efficient robot controllers in communicating rovers, flocking drones, plant robots, and modular robots. In the meanwhile, robotics is witnessing a profound transformation with the exploration of novel soft actuators, stretchable sensors, variable-stiffness bodies, and unconventional physical interactions. In these soft robots, just like in biological systems, the traditional distinction between body and intelligence is blurred. Intelligent and adaptive properties of these novel soft robots emerge from the co-design of morphology, materials, and computation. Evolutionary computation is a powerful method for exploring this complex space and generating novel soft robots. The success of this endeavor will depend on at least three factors: the definition of suitable components and models, the design of novel soft-physics simulators, and the availability of sufficient computing power. Recent progress on all these fronts makes this field one of the most promising and exciting research areas in artificial intelligence.
Abstract: Evolutionary computation has been successfully used for understanding the emergence of a wide range of biological intelligent behaviors for which there is no fossil record, such as altruism, division of labor, communication, non-deterministic behavior, and reward-based learning. These methods have also been used for generating efficient robot controllers in communicating rovers, flocking drones, plant robots, and modular robots. In the meanwhile, robotics is witnessing a profound transformation with the exploration of novel soft actuators, stretchable sensors, variable-stiffness bodies, and unconventional physical interactions. In these soft robots, just like in biological systems, the traditional distinction between body and intelligence is blurred. Intelligent and adaptive properties of these novel soft robots emerge from the co-design of morphology, materials, and computation. Evolutionary computation is a powerful method for exploring this complex space and generating novel soft robots. The success of this endeavor will depend on at least three factors: the definition of suitable components and models, the design of novel soft-physics simulators, and the availability of sufficient computing power. Recent progress on all these fronts makes this field one of the most promising and exciting research areas in artificial intelligence.
