Method
Reinforcement Learning
Learning placement/sequencing policies from reward signals.
Also called: Reinforcement Learning · RL · 심층 강화학습
A learning-based approach in which a policy for selecting and placing pieces is learned from a reward signal (e.g. utilization). Packing and nesting results have been reported with RL-based methods under specific benchmark conditions; this is not a claim of state-of-the-art or production readiness. See the evidence policy for how such unverified claims are phrased.
Claims & evidence
Every relationship is a claim with an evidence grade; applicable problem-to-problem relationships also carry an equivalence level. See the evidence policy.
No claims recorded yet.