Abstract
Abstract Behavioral diversity is an essential feature
of living systems, enabling them to exhibit adaptive
behavior in hostile and dynamically changing
environments. However, traditional engineering
approaches strive to avoid, or suppress, the behavioral
diversity in artificial systems to achieve high
performance in specific environments for given tasks.
The goals of this research include understanding how
living systems exhibit behavioral diversity and using
these findings to build lifelike robots that exhibit
truly adaptive behaviors. To this end, we have focused
on one of the most primitive forms of intelligence
concerning behavioral diversity, namely, a plasmodium
of true slime mold. The plasmodium is a large
amoeba-like unicellular organism that does not possess
any nervous system or specialized organs. However, it
exhibits versatile spatiotemporal oscillatory patterns
and switches spontaneously between these. Inspired by
the plasmodium, we built a mathematical model that
exhibits versatile oscillatory patterns and
spontaneously transitions between these patterns. This
model demonstrates that, in contrast to coupled
nonlinear oscillators with a well-designed complex
diffusion network, physically interacting
mechanosensory oscillators are capable of generating
versatile oscillatory patterns without changing any
parameters. Thus, the results are expected to shed new
light on the design scheme for lifelike robots that
exhibit amazingly versatile and adaptive behaviors.
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