Tootfinder

Deep Hedging Under Non-Convexity: Limitations and a Case for AlphaZero
Matteo Maggiolo, Giuseppe Nuti, Miroslav \v{S}trupl, Oleg Szehr
https://arxiv.org/abs/2510.01874 https://

Deep Hedging Under Non-Convexity: Limitations and a Case for AlphaZero
This paper examines replication portfolio construction in incomplete markets - a key problem in financial engineering with applications in pricing, hedging, balance sheet management, and energy storage planning. We model this as a two-player game between an investor and the market, where the investor makes strategic bets on future states while the market reveals outcomes. Inspired by the success of Monte Carlo Tree Search in stochastic games, we introduce an AlphaZero-based system and compare i…

3D-CovDiffusion: 3D-Aware Diffusion Policy for Coverage Path Planning
Chenyuan Chen, Haoran Ding, Ran Ding, Tianyu Liu, Zewen He, Anqing Duan, Dezhen Song, Xiaodan Liang, Yoshihiko Nakamura
https://arxiv.org/abs/2510.03011

3D-CovDiffusion: 3D-Aware Diffusion Policy for Coverage Path Planning
Diffusion models, as a class of deep generative models, have recently emerged as powerful tools for robot skills by enabling stable training with reliable convergence. In this paper, we present an end-to-end framework for generating long, smooth trajectories that explicitly target high surface coverage across various industrial tasks, including polishing, robotic painting, and spray coating. The conventional methods are always fundamentally constrained by their predefined functional forms, whic…