13 papers
One More Time: Revisiting Neural Quantum States from a Reinforcement Learning Perspective
Juan AgustÃn Duque, Sergio GarcÃa Heredia, Vinicius Hernandes +4
Neural quantum states (NQS) provide a flexible and scalable framework for approximating quantum many-body wavefunctions. Among NQS parameterizations, autoregressive models are espe…
Representation Learning Enables Scalable Multitask Deep Reinforcement Learning
Johan Obando-Ceron, Lu Li, Scott Fujimoto +3
Scaling reinforcement learning (RL) to diverse multitask settings remains a central challenge. While recent advances in model-based RL achieve strong performance, they rely on plan…
Local Guidance, Global Impact: Gaussian-Reshaped Trust Region Unlocks Behavior Transitions
Bingxu Liu, Jiashun Liu, Johan Obando-Ceron +5
While Proximal Policy Optimization (PPO) demonstrates strong performance in stationary settings, we show that its standard optimization paradigm struggles in continual and non-stat…
Generative Adversarial Post-Training Mitigates Reward Hacking in Live Human-AI Music Interaction
Yusong Wu, Stephen Brade, Aleksandra Teng Ma +6
Most applications of generative AI involve a sequential interaction in which a person inputs a prompt and waits for a response, and where reaction time and adaptivity are not impor…
Evolution Strategies at the Hyperscale
Bidipta Sarkar, Mattie Fellows, Juan Agustin Duque +17
Evolution Strategies (ES) is a class of powerful black-box optimisation methods that are highly parallelisable and can handle non-differentiable and noisy objectives. However, naï…
Towards Sustainable Investment Policies Informed by Opponent Shaping
Juan Agustin Duque, Razvan Ciuca, Ayoub Echchahed +2
Addressing climate change requires global coordination, yet rational economic actors often prioritize immediate gains over collective welfare, resulting in social dilemmas. InvestE…