Action Policies Research Articles

HiSOMA: A hierarchical multi-agent model integrating self-organizing neural networks with multi-agent deep reinforcement learning

Multi-agent deep reinforcement learning (MADRL) has shown remarkable advancements in the past decade. However, most current MADRL models focus on task-specific short-horizon problems involving a small number of agents, limiting their applicability to long-horizon planning in complex environments. Hierarchical multi-agent models offer a promising solution by organizing agents into different levels, effectively addressing tasks with varying planning horizons. However, these models often face constraints related to the number of agents or levels of hierarchies. This paper introduces HiSOMA, a novel hierarchical multi-agent model designed to handle long-horizon, multi-agent, multi-task decision-making problems. The top-level controller, FALCON, is modeled as a class of self-organizing neural networks (SONN), designed to learn high-level decision rules as internal cognitive codes to modulate middle-level controllers in a fast and incremental manner. The middle-level controllers, MADRL models, in turn receive modulatory signals from the higher level and regulate bottom-level controllers, which learn individual action policies generating primitive actions and interacting directly with the environment. Extensive experiments across different levels of the hierarchical model demonstrate HiSOMA’s efficiency in tackling challenging long-horizon problems, surpassing a number of non-hierarchical MADRL approaches. Moreover, its modular design allows for extension into deeper hierarchies and application to more complex tasks with heterogeneous controllers. Demonstration videos and codes can be found on our project web page: https://smu-ncc.github.io.

Gender Disparity in Principal Officers’ Positions in Nigerian Universities: Implications for Educational Planners and Administrators

The study investigates the gender disparities in leadership positions within Nigerian universities, focusing on principal officers such as Vice-Chancellors, Deputy Vice-Chancellors, Registrars, Bursars, and Librarians. Analyzing data from the 2019 Nigerian University System Statistical Digest. The study employs ANOVA statistics to establish the statistical significance of these disparities and highlights the need for targeted interventions to rectify these imbalances. The research reveals striking imbalances in gender representation across these roles. The findings demonstrate that, despite notable progress in some areas, women remain significantly underrepresented in key leadership positions, with a pronounced gender gap persisting across various types of universities (federal, state, and private). The recommendations offered encompass gender-neutral selection processes, affirmative action policies, leadership development programs, mentorship initiatives, educational campaigns, and regular data collection to promote gender equity. These proposed strategies aim to create a more inclusive academic environment where leadership positions are accessible to all based on qualifications and merit, ultimately fostering diversity and enriching the higher education landscape in Nigeria.

Understanding Students’ Attitudes Towards Affirmative Action Policy in Higher Education in India

To mitigate the severe educational horizontal inequalities in India, affirmative action (AA) measures in higher education (HE) have been implemented for socially excluded groups, such as the Scheduled Castes (former “untouchables”), the scheduled tribes (whose status resembles indigenous groups in other countries), and other classes lower in the caste hierarchy. Despite the introduction of AA measures, societal attitudes generally remain resistant to caste‐based reservation policies. Interestingly, very few studies in India have examined AA support among the most directly affected group of people when it comes to AA measures in HE—college students. The current article aims to fill this gap. It asks: Which factors (such as students’ background characteristics, pre‐college credentials, experience in college, and caste‐based beliefs) underlie college students’ attitudes (support or resistance) towards AA? This study builds on a large‐scale survey conducted among 3200 students studying in 12 public higher education institutions across six provinces in India. The results of the empirical analysis indicate that students’ attitudes towards AA are shaped and influenced by their social identity and educational experiences in college. It is also noteworthy that caste‐based biases and prejudices affect students’ attitudes particularly and may explain opposition to AA.

Demographic dynamics and rights-based population policies for effective climate change adaptation and mitigation

Contemporary demographic patterns differ widely between countries. The combined trajectories of population growth and the climate crisis will lead to a redistribution of people on the planet, with urbanization offering both promise and risk for efforts to mitigate climate change. While all individuals contribute to emissions, they do not do so in the same ways, and nor are they affected proportionately. In this paper, we argue for a more evidence-based use of demographic data to bolster the effectiveness of climate change mitigation and adaptation to reduce both population risks and vulnerabilities, and underscore the important role of rights-based, people-centred population policies in climate action. In doing so, we present fresh perspectives for policymakers and researchers dedicated to sustainable development. By aligning adaptation and mitigation strategies with current and future population dynamics, we can identify interventions that create more resilient, equitable and greener societies.

AoI minimization of ambient backscatter-assisted EH-CRN with cooperative spectrum sensing

To evaluate the timeliness and freshness of information from energy-constrained devices, we minimize the weighted average age of information (AoI) of the ambient backscatter-assisted energy harvesting cognitive radio network (AB-EH-CRN), where secondary transmitters (STs) follow the non-orthogonal multiple access (NOMA) strategy to transmit status updates. The secondary receiver (SR) schedules the selected actions for STs to perform spectrum access, and receives status updates from them. We formulate the AoI minimization problem where the action selection and transmission power of STs are considered as variables. To exploit spectrum resources in the AB-EH-CRN with unknown signal-to-noise ratios (SNRs) at the STs, we propose the deep neural network (DNN)-based cooperative spectrum sensing (CSS), and adopt an energy threshold approach for STs to determine the energy allocation between spectrum sensing (SS) and packet transmission. Moreover, we address the AoI minimization problem by the proposed hybrid action and energy penalty deep deterministic policy gradient (HAEP-DDPG) algorithm, which adapts to the hybrid continuous and discrete action spaces. Simulation results validate the advantage of the proposed HAEP-DDPG algorithm compared with comparison schemes in terms of AoI.

Configurational pathways to innovation capability enhancement in high-tech enterprises: a perspective from technological innovation network

PurposeHigh-tech enterprises, as the national innovation powerhouses, have garnered considerable interest, particularly regarding their technological innovation capabilities. Nevertheless, prevalent research tends to spotlight the impact of individual factors on innovative behavior, with only a fraction adopting a comprehensive viewpoint, scrutinizing the causal amalgamations of precursor conditions influencing the overall innovation proficiency of high-tech enterprises.Design/methodology/approachThis paper employs a hybrid approach integrating necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA) to examine the combinatorial effects of antecedent factors on high-tech enterprises' innovation output. Our analysis draws upon data from 46 listed Chinese high-tech enterprises. To promote technological innovation within high-tech enterprises, we introduce a novel perspective that emphasizes technological innovation networks, grounded in a network agents-structure-environment framework. These antecedents are government subsidy, tax benefits, customer concentration, purchase concentration rate, market-oriented index and innovation environment.FindingsThe findings delineate four configurational pathways leading to high innovative output and three pathways resulting in low production.Originality/valueThis study thereby enriches the body of knowledge around technological innovation and provides actionable policy recommendations.

Plastic Politics of Delay: How Political Corporate Social Responsibility Discourses Produce and Reinforce Inequality in Plastic Waste Governance

Abstract As the global plastics pollution crisis grows in severity and complexity, diverse solutions are being proposed across the public and private sectors. Notably, multinational corporations (MNCs) from the petrochemical and consumer goods sectors have become increasingly involved. From providing recycling infrastructure to directly participating in drafting action plans and policies, MNCs are engaging as political actors in plastics waste governance, influencing discourses and actions globally, a process referred to as political corporate social responsibility (CSR). In this article, I examine Coca-Cola’s World Without Waste initiative as a case study of this process. I evaluate how Coca-Cola frames the problems of plastics waste, their solutions, and the roles that Coca-Cola asserts within this complex, transboundary environmental governance issue. Borrowing from literature on corporate climate delay tactics, I demonstrate how the initiative implements discourses and practices of delayed action, hindering comprehensive governance strategies. Through this analysis, I argue that political CSR actions can exacerbate the global plastics pollution crisis through ineffective and inequitable waste governance approaches that perpetuate uneven plastics pollution burdens.

‘Sit down and thrash it out’: opportunities for expanding ethics consultation during conflict resolution in long-term care

Objective: To identify the frequency and nature of care conflict dilemmas that United States long-term care providers encounter, response strategies, and use of ethics resources to assist with dispute resolution. Design: An online cross-sectional survey was distributed to the Society for Post-Acute and Long-Term Care Medicine (AMDA). Results: Two-thirds of participants, primarily medical directors, have rejected surrogate instructions and 71% have managed family conflict. Conflict over treatment decisions and issues interpreting advance directives were frequently reported. Half of facilities lack a formal dispute mediation policy. Only five respondents have called an ethics consult for assistance. Conclusion: Ethically tense care conflicts commonly arise in long-term and post-acute care facilities. Few facility procedures incorporate ethics resources into actual practice. Recommendations are made to create actionable policy, increase access to ethics services, and support staff skill development in order to improve the end-of-life care experiences for patients, families, and care facility staff.

Urban density and the urban forest: How well are cities balancing them in the context of climate change?

Urban forests are gaining recognition as a nature-based solution to climate change and other social-environmental issues in cities. Yet, the integration of urban forests may conflict with other climate measures such as urban densification, which may create hostile growing conditions for trees and lead to tree decline or loss. While previous studies have identified conflicts between densification and urban forests, there is a lack of research mapping the relationships among climate action, urban planning, and urban forest policies. This study involved semi-structured interviews with 14 key informants in Metro Vancouver, Canada, a rapidly-densifying region.Twenty-six trade-offs and 24 synergies were identified in five areas/sectors, such as (re)development and infrastructure. While strategic policies often highlighted synergies, policy implementation processes and outcomes often encountered trade-offs due to factors such as limited budgets and low political priority. Notably, most trade-offs and synergies were found in the same areas - (re)development and infrastructure - and shared the same contributing factors, such as political priority of urban forestry, suggesting areas of opportunity to transform trade-offs into synergies through appropriate planning and monitoring. The study also highlighted the need for further research on the interactions and impacts among municipal policies for more effective implementation and outcomes.

프랑스 민법에서 소멸시효 완성의 효과

In this article, the author examines the effects of liberative prescription in French civil law and its implications for the interpretation of the Korean Civil Code. The conclusions can be summarized as follows:
 1. The question of whether a right is extinguished by the expiration of a prescription period, whether the expiration must be pleaded as a defense, and who may plead it, is a long-standing issue that has been debated since Roman law.
 2. The provisions of the French Civil Code regarding the effects of liberative prescription generally align with the absolute theory in Korean law. The expiration of a prescription period results in the extinguishment of the right or its action, allowing the benefit of prescription to be claimed by other interested parties in addition to the debtor. However, the court cannot consider it ex officio, and restitution is not allowed if the extinguished obligation has been paid. In contrast to our absolute theory, French law differs in that the debtor's other creditors can claim the benefit of prescription only to the extent that the debtor is insolvent.
 3. The following observations can be drawn from French civil law for the interpretation of the Korean Civil Code. First, the necessity of claiming the benefit of prescription is closely related to the possibility of its waiver, and under the absolute theory, therefore, the defense of prescription is treated as a procedural matter concerning the extinguished rights. Second, in view of Article 404 (2), a debtor should be able to contest a defense of prescription against the oblique action of their creditor's creditor if the latter's claim is already time-barred. Third, claiming the benefit of prescription by other creditors of the debtor in question, including mortgagees in inferior rankings, is permissible, but only to the extent that the debtor is insolvent, aligning with the policy of the oblique action.

Climate change and zoonotic diseases: a conceptual framework for predicting and managing health risks in the USA

The executive summary will provide a concise overview of the conceptual framework aimed at understanding the relationship between climate change and zoonotic diseases in the USA. It will highlight the significance of addressing this issue, the objectives of the framework, expected outcomes, and the proposed methodology for research and implementation. It encapsulates the essence of the proposed framework, highlighting its significance, objectives, methodology, and expected outcomes. Climate change poses a significant threat to public health, exacerbating the emergence and transmission of zoonotic diseases across the USA. This executive summary underscores the critical need for a proactive approach to understanding and managing the complex interplay between climate change and zoonotic diseases to safeguard the health of communities. The framework aims to address this pressing issue by elucidating the mechanisms through which climate change influences the dynamics of zoonotic diseases. By integrating multidisciplinary research, predictive modeling, and public health strategies, the framework seeks to enhance the nation's capacity to predict, prevent, and mitigate the health risks associated with climate change-driven zoonotic diseases. Key objectives of the framework include developing predictive models to identify high-risk areas and vulnerable populations, elucidating the pathways of disease transmission, and proposing evidence-based interventions to mitigate health risks. By fostering collaboration among researchers, policymakers, and public health practitioners, the framework aims to translate research findings into actionable strategies and policies that protect public health and promote resilience in the face of climate change. Expected outcomes of the framework include improved understanding of the complex relationship between climate change and zoonotic diseases, enhanced surveillance and early warning systems, and informed decision-making to guide public health interventions. Ultimately, the framework seeks to empower communities and decision-makers with the knowledge and tools needed to adapt to changing environmental conditions and mitigate the health impacts of zoonotic diseases in the USA.

Equity and access in higher education: Legal perspectives and management strategies

Ensuring equity and access in higher education has become a paramount concern for institutions, policymakers, and stakeholders worldwide. This review delves into the legal frameworks and management strategies essential for promoting equity and access within higher education systems. Firstly, legal perspectives provide a foundation for understanding the rights and responsibilities of both institutions and students. Various laws and regulations, including affirmative action policies, anti-discrimination statutes, and accessibility mandates, shape the legal landscape of higher education equity. Analyzing landmark court cases and legislative acts elucidates the evolving nature of these legal frameworks and their implications for fostering inclusive environments. Secondly, effective management strategies play a pivotal role in translating legal mandates into actionable initiatives. Institutional leaders must prioritize diversity, equity, and inclusion (DEI) efforts across all facets of academic and administrative operations. Implementing proactive recruitment and retention practices, establishing support services for underrepresented groups, and fostering a culture of inclusivity are among the key strategies employed to enhance accessibility and promote equity. Moreover, leveraging technology and data analytics can facilitate evidence-based decision-making and resource allocation, thereby addressing disparities in educational outcomes. Collaborative partnerships with community organizations, government agencies, and industry stakeholders also amplify the impact of equity initiatives and expand access to higher education opportunities. Navigating the complex intersection of legal requirements and management imperatives is essential for advancing equity and access in higher education. By embracing a holistic approach that combines legal compliance with strategic planning and proactive interventions, institutions can foster environments where all individuals have equitable opportunities to succeed and thrive academically.

Offsetting Distortion Effects of Head Starts on Incentives in Tullock Contests

Abstract In this study, we examine a contest scenario where each player possesses a distinct head start that skews their chances of winning, thereby creating incentive distortions from the efficient level and adversely affecting the contest designer. While affirmative action policies offer a straightforward solution to counteract these distortions, their implementation may not always be viable in real-life applications. We characterize the unique class of non-discriminatory contest success functions (CSF) that enables to achieve an efficient level of effort when there are two players. Additionally, we demonstrate that achieving a symmetric equilibrium is unattainable without affirmative action when the contest involves more than two players.

Information avoidance in school choice

I explain puzzles in the school assignment literature using a many-to-one matching model in which participants on one side of the market, the students, are endowed with ego-utilities à la Köszegi (2006). Ego concerns generate a form of information avoidance that results in non-truthful participation in DA matching mechanisms. In particular, students' best replies may be non-monotonic in school ranks. I show that truthful reporting can be restored by imposing a limit on the measure of students that a school can deem acceptable. Furthermore, students may be sensitive to signal garbling, in the sense of Blackwell (1953). In terms of policy, the results imply that admission committees' reliance on application dimensions that are seemingly weak proxies of academic performance may be beneficial. Other implications suggest that affirmative action policies might be beneficial. However, when students' best replies exhibit non-monotonicity in schools' selectivity, such policies might backfire.

The Socio-Economic Impact of Judicial Verdicts

The socio-economic impact of judicial verdicts is a critical area of inquiry within contemporary legal scholarship and governance discourse. This research paper delves into the intricate dynamics surrounding judicial decisions, aiming to unravel their implications for economic development, social cohesion, and democratic governance. Grounded in interdisciplinary dialogue and empirical analysis, the study offers insights that extend beyond academic inquiry to inform policy deliberations and practical interventions.
 Against the backdrop of rapid globalization and evolving legal frameworks, understanding the complexities of judicial verdicts assumes paramount importance. This research endeavors to comprehensively explore the socio-economic dimensions underpinning judicial decisions, shedding light on disparities in access to justice, economic repercussions, and societal implications. Through a systematic examination of diverse legal systems and socio-cultural contexts, the study elucidates the multi-faceted nature of judicial impact on society.
 The objectives of the research are structured to address critical gaps in understanding the socio-economic impact of judicial verdicts and to contribute meaningfully to scholarly discourse and policy deliberations in the field of law and governance. These objectives encompass examining socio-economic dimensions, identifying disparities in access to justice, assessing economic consequences, exploring social dynamics and public perceptions, and providing actionable policy recommendations and implications.
 The significance of this research lies in its potential to generate knowledge, inform policy change, and foster inclusive governance practices that uphold principles of justice, equity, and human rights. By advancing interdisciplinary dialogue, empirical rigor, and policy relevance, the study serves as a catalyst for positive transformation within legal systems and societal institutions, contributing to the advancement of a more just, equitable, and democratic world.
 While the research acknowledges certain limitations, including geographical and jurisdictional constraints, data availability and reliability, interdisciplinary complexity, and temporal constraints, it seeks to provide valuable insights and contributions to scholarly discourse and policy deliberations. Through rigorous analysis and engagement with international standards of scholarly inquiry, the research aims to foster informed decision-making and inclusive governance practices at the intersection of law, society, and governance.

Human skill knowledge guided global trajectory policy reinforcement learning method.

Traditional trajectory learning methods based on Imitation Learning (IL) only learn the existing trajectory knowledge from human demonstration. In this way, it can not adapt the trajectory knowledge to the task environment by interacting with the environment and fine-tuning the policy. To address this problem, a global trajectory learning method which combinines IL with Reinforcement Learning (RL) to adapt the knowledge policy to the environment is proposed. In this paper, IL is proposed to acquire basic trajectory skills, and then learns the agent will explore and exploit more policy which is applicable to the current environment by RL. The basic trajectory skills include the knowledge policy and the time stage information in the whole task space to help learn the time series of the trajectory, and are used to guide the subsequent RL process. Notably, neural networks are not used to model the action policy and the Q value of RL during the RL process. Instead, they are sampled and updated in the whole task space and then transferred to the networks after the RL process through Behavior Cloning (BC) to get continuous and smooth global trajectory policy. The feasibility and the effectiveness of the method was validated in a custom Gym environment of a flower drawing task. And then, we executed the learned policy in the real-world robot drawing experiment.

What Breast Cancer Screening Program do Rural Women Prefer? A Discrete Choice Experiment in Jiangsu, China.

Chinese rural women aged 35-64 years are encouraged to complete breast cancer screening (BCS) free of charge. However, it is challenging to reach a satisfying BCS uptake rate. In this study, rural women's preferences and preferences heterogeneity were measured for the development of strategies to enhance participation in BCS. A cross-sectional survey with a discrete choice experiment (DCE) was conducted via convenience sampling via face-to-face interviews in Jiangsu, China. Six DCE attributes were identified through a systematic literature review; our previous study of Chinese rural women's BCS intentions; a qualitative work involving in-depth interviews with rural women (n = 13), medical staff (n = 4), and health care managers (n = 2); and knowledge of realistic and actionable policy. The D-efficient design was generated using Ngene 1.3.0. A mixed logit model (MXL) in Stata 18.0 was used to estimate the main effect of attribute levels on rural women's preferences. The relative importance and willingness to utilize BCS services (WTU) were also estimated. The heterogeneous preferences were analyzed by a latent class model (LCM). Sociodemographic status was used to predict the characteristics of class membership. The WTU for different classes was also calculated. A total of 451 rural women, aged 35-64 years, were recruited. The MXL results revealed that the screening interval (SI) was the most important attribute for rural women with regard to utilizing BCS services, followed by the level of screening, the attitude of medical staff, ways to get knowledge and information, people who recommend screening, and time spent on screening (TSS). Rural women preferred a BCS service with a shorter TSS; access to knowledge and information through multiple approaches; a shorter SI; a recommendation from medical staff or workers from the village or community, and others; the enthusiasm of medical staff; and medical staff with longer tenures in the field. Two classes named "process driven" and "efficiency driven" were identified by the preference heterogeneity analysis of the LCM. There is a higher uptake of breast cancer screening when servicesare tailored to women's preferences. The screening interval was the most important attribute for rural women in China with a preference for a yearly screening interval versus longer intervals.

Autonomous Behavior Selection For Self-driving Cars Using Probabilistic Logic Factored Markov Decision Processes

ABSTRACT We propose probabilistic logic factored Markov decision processes (PL-fMDPs) as a behavior selection scheme for self-driving cars. Probabilistic logic combines logic programming with probability theory to achieve clear, rule-based knowledge descriptions of multivariate probability distributions, and a flexible mixture of deductive and probabilistic inferences. Factored Markov decision processes (fMDPs) are widely used to generate reward-optimal action policies for stochastic sequential decision problems. For evaluation, we developed a simulated self-driving car with reliable modules for behavior selection, perception, and control. The behavior selection module is composed of a two-level structure of four action policies obtained from PL-fMDPs. Three main tests were conducted focused on the selection of the appropriate actions in specific driving scenarios, and the overtaking of static obstacle vehicles and dynamic obstacle vehicles. We performed 520 repetitions of these tests. The self-driving car completed its task without collisions in 99.2% of the repetitions. Results show the suitability of the overall self-driving strategy and PL-fMDPs to construct safe action policies for self-driving cars.

Trends in Admittance and Equity in Higher Education: Are Male Students in Uganda Disadvantaged?

The purpose of this study was to assess the impact of trends in admittance and equity in higher education. Using Qualitative approach in data collection, this study answered the following questions: Are Male students currently disadvantaged in admittance to higher education in favour of female students? What is the impact this imbalance in relation to job market demands for skilled labour from both sexes? What long-term initiatives might significantly increase the number of male students admitted to higher education institutions for gender equity? The findings were that the available data on trends in admitting students in higher institutions show an almost equal number of the ratio of females to male with some exceptional institutions where female ratios have exceeded male ratios. It is recommended that the government should review affirmative action policies so that the recruitment does not favor one gender as it were before the programs.

Foundations mostly staying the course in response in light of affirmative action rulings

New research from the Center for Effective Philanthropy concludes that U.S. grantmaking foundations are largely holding steady in their support for racial equity initiatives despite a pair of rulings from the Supreme Court that overturned affirmative action policies in higher education.