This paper presents an energy-based approach for simulating virtual creatures, advocating for a shift from traditional monolithic physics engines to a more flexible implementation approach centered on energy minimization and automatic differentiation. By integrating insights from established disciplines alongside emerging concepts such as scale-free cognition, this approach enables a comprehensive modeling of behaviors, where everything from basic physical phenomena, such as inertia and elasticity, to more complex behaviors, such as robust locomotion, can be interpreted as goal-directed behavior.

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General Conference: Accepted oral presentations
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© 2024 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license
2024
Massachusetts Institute of Technology
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Issue Section:
General Conference: Accepted oral presentations