Abstract: Multi-objective reinforcement learning (MORL) is a structured approach for optimizing tasks with multiple objectives. However, it often relies on pre-defined reward functions, which can be ...

RLP uses a single network (shared parameters) to (1) sample a CoT policy 𝜋 𝜃 ( 𝑐 𝑡 ∣ 𝑥 < 𝑡 ) π θ (c t ∣x <t ) and then (2) score the next token 𝑝 𝜃 ( 𝑥 𝑡 ∣ 𝑥 < 𝑡 , 𝑐 𝑡 ) p θ (x t ∣x <t ...

Rick: A lot of parents and educators may be familiar with the phrase “mastery learning” but not have a clear idea what it means in practice. What is it exactly? Scott: My journey began in 2012 when I ...

The Recentive decision exemplifies the Federal Circuit’s skepticism toward claims that dress up longstanding business problems in machine-learning garb, while the USPTO’s examples confirm that ...

PolyRL is an open-source framework for reinforcement learning-based molecular generation, designed to accelerate the discovery of polymeric membranes for CO₂/N₂ gas separation. It integrates multiple ...

The Centre for Advanced Research Computing (ARC) of University College London (UCL) designs and delivers continuing professional development offerings in digital research practices to colleagues and ...

1 Research Institute of Petroleum Exploration and Development, PetroChina, Beijing, China 2 Faculty of Petroleum, China University of Petroleum-Beijing at Karamay, Karamay, China Lithology ...

To be useful, the assessments you give students must meet two conditions. First, assessments must be appropriately challenging at the moment when they are given. A question that’s clearly too hard or ...