Quality Diversity for Reliable Data Driven Time-Use Optimization

arXiv:2608.05230 · stat.ML, cs.AI, cs.LG, cs.NE · Submitted 2026-08-05 · Read on arXiv

Aneta Neumann, Ty Stanford, Dorothea Dumuid, Frank Neumann

stat.ML, cs.AI, cs.LG, cs.NE

Submitted: 2026-08-05

Comments: To appear in the Proceedings of Parallel Problem Solving from Nature (PPSN 2026)

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Quality Diversity — 32× in this paper
• Composition — 20× in this paper · explained in 2 episodes
• Uncertainty Quantification — 12× in this paper · explained in 9 episodes
• Objective Function — 8× in this paper · explained in 2 episodes
• Longitudinal Study of Australian Children — 2× in this paper
• Robustness — 2× in this paper · explained in 6 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• ObjectiveBased Behavioral Spaces — 1× in this paper
• Predictive Modeling — 1× in this paper · explained in 3 episodes
• Surrogate Model — 1× in this paper · explained in 3 episodes
• Variable-Based Behavioral Spaces — 1× in this paper

Sources

• Illuminating search spaces by mapping elites

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