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Integrating the Cognitive with the Physical: Musical Path Planning for an Improvising Robot

AAAI 2017 · Multi-agent systems and games › Human-AI and goal-conditioned · approach: Embodied agent learning · 4 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Replace greedy per-note arm selection with global Viterbi path planningShimon marimba robot · 100 pre-composed note sequencesoctave transpose rate: 39.2% -> 11.1%Helped
Replace greedy per-note arm selection with global Viterbi path planningShimon marimba robot · 100 pre-composed note sequencesnote drop rate: 14.9% -> 1.7%Helped

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