Biological agents have bodies that are composed mostly of soft tissue. Researchers have resorted to soft bodies to investigate Artificial Life (ALife)-related questions; similarly, a new era of soft-bodied robots has just begun. Nevertheless, because of their infinite degrees of freedom, soft bodies pose unique challenges in terms of simulation, control, and optimization. Herein I propose a novel soft-bodied agents formalism, namely, pressure-based soft agents (PSAs): spring-mass membranes containing a pressurized medium. Pressure endows the agents with structure, while springs and masses simulate softness and allow the agents to assume a large gamut of shapes. PSAs actuate both locally, by changing the resting lengths of springs, and globally, by modulating global pressure. I optimize the controller of PSAs for a locomotion task on hilly terrain, an escape task from a cage, and an object manipulation task. The results suggest that PSAs are indeed effective at the tasks, especially those requiring a shape change. I envision PSAs as playing a role in modeling soft-bodied agents, such as soft robots and biological cells.
Keywords: Embodied cognition; evolutionary robotics; shape change; soft robotics.
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