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Target-oriented policy diffusion analysis: a case study of China’s information technology policy
Current quantitative research on policy diffusion tends to focus on the citation relationship between policies, while ignoring the nature of policy...
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Cautious policy programming: exploiting KL regularization for monotonic policy improvement in reinforcement learning
In this paper, we propose cautious policy programming (CPP), a novel value-based reinforcement learning (RL) algorithm that exploits the idea of...
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Off-policy and on-policy reinforcement learning with the Tsetlin machine
The Tsetlin Machine is a recent supervised learning algorithm that has obtained competitive accuracy- and resource usage results across several...
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Policy citations of scientometric articles: an altmetric study
Policy citations are considered as one of the important indicators of the societal impact of research. Scientometrics is a field that, among other...
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Policy-based optimization: single-step policy gradient method seen as an evolution strategy
This research reports on the recent development of black-box optimization methods based on single-step deep reinforcement learning and their...
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TFPsocialmedia: a public dataset for studying Turkish foreign policy
ObjectivesThis data note introduces the TFPsocialmedia dataset, designed to aid social media researchers investigating Turkish Foreign Policy (TFP)....
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IOB: integrating optimization transfer and behavior transfer for multi-policy reuse
Humans have the ability to reuse previously learned policies to solve new tasks quickly, and reinforcement learning (RL) agents can do the same by...
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Size matters: contextual factors in local policy translations of National School Digitalisation Policy
National policies on school digitalisation take shape in their local contexts. Consequently, to understand the outcome of national policy, the local...
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Algorithmic governance and AI: balancing innovation and oversight in Indonesian policy analyst
The objective of this study is to examine the effects of generative artificial intelligence (AI) tools, with a specific focus on ChatGPT, on the...
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Intelligent analysis of android application privacy policy and permission consistency
With the continuous development of mobile devices, mobile applications bring a lot of convenience to people’s lives. The abuse of mobile device...
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Online Pareto optimal control of mean-field stochastic multi-player systems using policy iteration
In this study, the Pareto optimal strategy problem was investigated for multi-player mean-field stochastic systems governed by Itô differential...
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Model gradient: unified model and policy learning in model-based reinforcement learning
Model-based reinforcement learning is a promising direction to improve the sample efficiency of reinforcement learning with learning a model of the...
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A certified access control policy language: TEpla
Access control is an information security process which guards protected resources against unauthorized access, as specified by restrictions in...
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Policy semantic networks associated with ICT utilization in Africa
Information and communications technology (ICT) research finds that greater utilization of ICTs leads to economic growth. This effect has led...
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Analyzing sentiments towards E-Levy policy implementation in Ghana using twitter data
A newly proposed or implemented government policy often encounters challenges. Ghanaian citizens have always look down negatively upon their...
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Policy regularization for legible behavior
In this paper we propose a method to augment a Reinforcement Learning agent with legibility. This method is inspired by the literature in Explainable...
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Difference rewards policy gradients
Policy gradient methods have become one of the most popular classes of algorithms for multi-agent reinforcement learning. A key challenge, however,...
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Empirical analysis of the impact of China’s carbon emissions trading policy using provincial-level data
Investigating the impact of carbon emissions trading policy and elucidating the underlying mechanisms are crucial for enhancing policy effectiveness...
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Towards Jum** Skill Learning by Target-guided Policy Optimization for Quadruped Robots
Endowing quadruped robots with the skill to forward jump is conducive to making it overcome barriers and pass through complex terrains. In this...
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Off-policy evaluation for tabular reinforcement learning with synthetic trajectories
This paper addresses the problem of offline evaluation in tabular reinforcement learning (RL). We propose a novel method that leverages synthetic...
