In many areas, practitioners seek to use observational data to learn a treatment assignment policy that satisfies application-specific constraints, such as budget, fairness, simplicity, or other functional form constraints. For example, policies may be restricted to take the form of decision trees ...
Robust Offline Policy Learning with Observational Data from Multiple Sources 来自 arXiv.org 喜欢 0 阅读量: 2 作者:AG Carranza,S Athey 摘要: We consider the problem of using observational bandit feedback data from multiple heterogeneous data sources to learn a personalized decision policy that ...
PMIC: Improving Multi-Agent Reinforcement Learning with Progressive Mutual Informarion Collaboration 499 37:00 基于离线强化学习和策略评估框架的在线红包分配策略研究 483 23:00 Offline Reinforcement Learning with Value-based Episodic Memory 605 14:00 ...
physicians should educate themselves on the curricula taught in their respective school districts in order to be more aware of the sexual and reproductive health information their patients are receiving. Furthermore, Primary Care Physicians should discuss gender and sexuality with all patients ...
effects. Claim 4 (that norms of prosocial behaviour are more effective when coupled with the expectation of social approval and modelled by in-group members who are central in social networks) was mostly tested on observational data, but the effect sizes found in these data were notably strong....
The next three articles in our collection tackle different aspects ofpolicy learning– an ever-popular topic with students and scholars alike, according to our readership data! These selected articles advance the dialogue on this important topic by exploring how learning may be fostered or constrained...
linked to older, 1970s-era concerns for a proper evaluation of policy outcomes. They also appear tied, however, to the much broader contemporary organizational and management studies concerned with knowledge and learning in organizations and whether such organizational knowing and learning can be ...
Air quality policy evaluation Machine learning Weather normalisation Augmented synthetic control Observational data analysis 1. Introduction Air pollution has emerged as biggest environmental risk to public health with major implications on economic development. There is growing evidence demonstrating the detrimen...
What learning models (eg, in-person, remote, hybrid) maximize learning and safety? How do implementation and outcomes differ across settings with varying resources? What academic, psychosocial, and health inequities are exacerbated by school disruptions due to COVID-19? What interventions are needed...
Political scientists are increasingly exhorted to ensure their research has policy ‘impact’, most notably via Research Excellence Framework (REF) impact case studies, and ‘pathways to impact’ statements in UK Research Council funding applications. Ye