A maximum entropy reinforcement learning framework generates realistic customer trajectories in retail spaces that match real data better than TSP or PNN heuristics and support more accurate layout optimization decisions.
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4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4representative citing papers
CAPSULE learns probabilistic control-affine dynamics offline to construct uncertainty-incorporating control barrier functions that enforce conservative safety constraints via online action correction in reinforcement learning.
QDHUAC is a distributional, target-free QD-RL method that enables stable high-UTD training and competitive performance on Brax locomotion tasks using far fewer environment steps than prior approaches.
RAMP learns numeric action models online via a DRL-planning feedback loop and outperforms PPO on IPC numeric domains in solvability and plan quality.
citing papers explorer
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Modelling Customer Trajectories with Reinforcement Learning for Practical Retail Insights
A maximum entropy reinforcement learning framework generates realistic customer trajectories in retail spaces that match real data better than TSP or PNN heuristics and support more accurate layout optimization decisions.
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CAPSULE: Control-Theoretic Action Perturbations for Safe Uncertainty-Aware Reinforcement Learning
CAPSULE learns probabilistic control-affine dynamics offline to construct uncertainty-incorporating control barrier functions that enforce conservative safety constraints via online action correction in reinforcement learning.
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Distributional Value Estimation Without Target Networks for Robust Quality-Diversity
QDHUAC is a distributional, target-free QD-RL method that enables stable high-UTD training and competitive performance on Brax locomotion tasks using far fewer environment steps than prior approaches.
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RAMP: Hybrid DRL for Online Learning of Numeric Action Models
RAMP learns numeric action models online via a DRL-planning feedback loop and outperforms PPO on IPC numeric domains in solvability and plan quality.