Reward - Science topic

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The smartphone has become an indispensable device in modern life, consequential psychosocial problems such as smartphone addiction have gained worldwide attention. The aim of the present study is to assess the relation between smartphone overuse and seeking pleasure linked with reward system overstimulation and dopa-mine continuous release. A surve...

A practice that involves switching jobs usually between public sector and private sector roles in the same domain, raising a risk of conflict of interest. The revolving door can be problematic because former private sector employees in the public sector may favour former employers in industry over the public interest, when public funds or concessio...

Abstract Background The medical profession is one of the most highly respected and desired professions among students worldwide, most likely because it provides opportunities for both a financially and socially rewarding career. However, while it has been quite established that factors such as self-interest, family pressure, friend pressure, and so...

p>Renal artery embolization is an interventional procedure used to treat conditions such as renal artery rupture and renal cancer. It offers advantages such as minimal damage, fast recovery, and low side effects. The implementation of robotic wire navigation in interventional surgery can effectively assist doctors in performing the procedure. Deep...

p>Renal artery embolization is an interventional procedure used to treat conditions such as renal artery rupture and renal cancer. It offers advantages such as minimal damage, fast recovery, and low side effects. The implementation of robotic wire navigation in interventional surgery can effectively assist doctors in performing the procedure. Deep...

not those aims are worthwhile. SER accepts that differences between student outcomes are largely determined by socioeconomic status and 'natural' factors, but maintains that schools can and do make a significant difference. It attempts to explain why and to what extent those differences vary from school to school and between countries. SER is a qua...

This study aims to determine the relationship between coaching behavior and extrinsic motivation toward the performance of student-athletes. Specifically, it sought to answer the following questions: What is the perception of student-athletes on coaching behavior in terms of preferred and required behavior? What is the perception of student-athlete...

Introduction Home visitor well-being is integral to delivering effective home visiting services and a core component of successful home visiting program implementation. While burnout (BO), compassion fatigue (CF), and compassion satisfaction (CS) have been studied extensively in physicians, nurses, and other health providers, little is known about...

This article presents a model for the comparison of plea bargain proposals. The use of the model increases the possibility of the satisfactory development of the negotiation of rewarded collaboration agreements recently permitted under Brazilian law. A novelty in the model is the objective consideration of society’s interest in adequately punishing...

Bitcoin-NG is an extensible blockchain protocol based on the same trust model as Bitcoin. It divides each epoch into one Key-Block and multiple Micro-Blocks, effectively improving transaction processing capacity. Bitcoin-NG adopts a special incentive mechanism (i.e., the transaction fees in each epoch are split to the current and next leader) to ma...

The powerful allure of social media platforms has been attributed to the human need for social rewards. Here, we demonstrate that the spread of misinformation on such platforms is facilitated by existing social 'carrots' (e.g., 'likes') and 'sticks' (e.g., 'dislikes') that are dissociated from the veracity of the information shared. Testing 951 par...

Objective Hospitals are frequently associated with poor working conditions that can lead to work stress and increase the risk for reduced employee well-being. Managers can shape and improve working conditions and thereby, the health of their teams. Thus, as a prerequisite, managers need to be aware of their employees’ stress levels. This study had...

Recently, compressive text summarisation offers a balance between the conciseness issue of extractive summarisation and the factual hallucination issue of abstractive summarisation. However, most existing compressive summarisation methods are supervised, relying on the expensive effort of creating a new training dataset with corresponding compressi...

Improving the decision-making capabilities of agents is a key challenge on the road to artificial intelligence. To improve the planning skills needed to make good decisions, MuZero's agent combines prediction by a network model and planning by a tree search using the predictions. MuZero's learning process can fail when predictions are poor but plan...

This research assessed the impacts of motivation on employees' performance in Kabalore district local government in Uganda. The researcher used a cross sectional research design. A sample size of 64 respondents was studied; the researcher used purposive and simple random sampling techniques to select the sample size. Questionnaire and interview gui...

Aquaponics offers a soilless farming ecosystem by merging modern hydroponics with aquaculture. The fish food is provided to the aquaculture, and the ammonia generated by the fish is converted to nitrate using specialized bacteria, which is an essential resource for vegetation. Fluctuations in the ammonia levels affect the generated nitrate levels a...

The use of game elements in learning tasks is thought to facilitate emotional and behavioral responses as well as learner engagement. So far, however, little is known about the underlying neural mechanisms of game-based learning. In the current study, we added game elements to a number line estimation task assessing fraction understanding and compa...

Background: Social touch is an integral part of social relationships and has been associated with reward. Major depressive disorder (MDD) is characterized by severe impairments in reward processing, but the neural effects of social touch in MDD are still elusive. In this study, we aimed to determine whether the neural processing of social touch is...

Psychological empowerment of customer service representatives (CSRs) is seen to play a considerable impact on enhancing service quality and customer satisfaction in the service-based industry. The objective of this paper is to explore the factors that influence CSRs' psychological empowerment to foster positive workplace outcomes. A qualitative des...

Nineteenth-century agricultural observers became increasingly disenchanted with land reclamation. Enormous expenditure by landlords such as the duke of Sutherland estates failed to create extensive, permanent 'improvements'. Other schemes to bring in external expertise and farming capital also appeared to stall, such as the Knight family's reclamat...

Analysis of demographic profiles at a STEM-focused institution documented that the institution has a high proportion of male faculty and administrative leadership and low retention of faculty from underrepresented groups. Our goal is to improve retention of university faculty and research staff by shifting from a culture of attrition to a culture o...

The brain regulates food intake in response to internal energy demands and the availability of food. However, can internal energy storage influence the kind of memory that is formed? We show that the duration of starvation determines whether Drosophila melanogaster forms appetitive short-term or long-term memory. The internal glycogen storage in th...

In the same way that the computer vision (CV) and natural language processing (NLP) communities have developed self-supervised methods, reinforcement learning (RL) can be cast as a self-supervised problem: learning to reach any goal, without requiring human-specified rewards or labels. However, actually building a self-supervised foundation for RL...

From last two decades globally two words are gaining more attention and those are sustainability and environmental concerns. Business organizations have a vital role to play in protection of environment by adopting green practices in each segment. Green supply chain practices could is one of them and have equivalent importance comparing to other on...

With the acceleration of Chinese industrialization, industrial wastewater is discharged in large quantities, leading to a groundwater environment with high ammonia nitrogen characteristics in many places, which seriously endangers people’s health and makes the treatment of ammonia nitrogen by enterprises an urgent issue. Therefore, based on the pri...

This research assessed the impacts of motivation on employees' performance in Kabalore district local government in Uganda. The researcher used a cross sectional research design. A sample size of 64 respondents was studied; the researcher used purposive and simple random sampling techniques to select the sample size. Questionnaire and interview gui...

The issue of management remuneration, particularly in the context of excessive risk-taking by bank managers, has been a subject of intense debate in Switzerland and Germany. This scientific essay examines the relationship between management remuneration structures and the principal-agent problem, with a focus on the impact of regulatory policies on...

Reinforcement learning (RL) is an effective approach to motion planning in autonomous driving, where an optimal driving policy can be automatically learned using the interaction data with the environment. Nevertheless, the reward function for an RL agent, which is significant to its performance, is challenging to be determined. The conventional wor...

We study zero-shot generalization in reinforcement learning - optimizing a policy on a set of training tasks such that it will perform well on a similar but unseen test task. To mitigate overfitting, previous work explored different notions of invariance to the task. However, on problems such as the ProcGen Maze, an adequate solution that is invari...

Learning causal relationships relies on understanding how often one event precedes another. To gain an understanding of how dopamine neuron activity and neurotransmitter release change when a retrospective relationship is degraded for a specific pair of events, we used outcome-selective Pavlovian contingency degradation in rats. Two cues were paire...

Penelitian ini membahas tentang “Kepemimpinan Transformatif Kepala Sekolah Dalam Meningkatkan Kemampuan Literasi Digital Tenaga Pendidik di SD Alkhairaat 1 Palu”. Penelitian ini bertujuan untuk menjawab fokus penelitian mengenai kepemimpinan transformatif kepala sekolah dalam meningkatkan kemampuan literasi digital tenaga pendidik di SD Alkhairaat...

In this research, we argue that conscientiousness can be a key factor in accounting for the racial pay gap among Black and White workers. Drawing from shifting standard and status characteristics theories and the literature on occupations, we propose that conscientiousness yields differential rewards for Blacks and Whites because of the incongruenc...

It is a critical challenge for model-free reinforcement learning to explore in sparse reward environments with advantage. Many current state-of-the-art approaches take the approach of designing intrinsic rewards to encourage exploration. However, when there are multiple new domains to explore in the environment, many approaches usually focus on one...

Adaptive sampling and mesh representation of images play an important role in image compression and vectorization. In this paper, a multi-points stochastic gradient multi-armed bandits algorithm, a generalization of the gradient bandit algorithm, is presented to adaptively sample points in images. By modeling the adaptive image sampling as a multi-...

Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder. Data on the role of transdiagnostic, intermediate phenotypes in ADHD-relevant characteristics and outcomes are needed to advance conceptual understanding and approaches to precision psychiatry. Specifically, the extent to which the association between neural response to re...

Ovim se radom istražuju povezanosti sudjelovanja u nastavnim i izvannastavnim glazbenim aktivnostima s procjenom kvalitete školskoga života učenika, tj. općim zadovoljstvom školom, školskim uspjehom i socijalnom integracijom učenika. U istraživanju su korišteni Upitnik kvalitete školskoga života (Quality of School Life) prilagođen na hrvatski jezik...

Attempts to obtain rewards are not always successful. Despite investing much time, effort, or money, sometimes individuals may not obtain any reward. Other times they may obtain some reward, but the obtained reward may be smaller than their initial investment, such as partial wins in gambling. It remains unclear how such ambiguous outcomes are appr...

Using reinforcement learning to control traffic signal systems has been discussed in recent years, but most works focused on simple scenarios such as a single crossroads, and the methods aiming at large-scale traffic scenarios face long-time training and suboptimal results. In this work, we develop a new multi-agent reinforcement model for large-sc...

Introduction - Porter and Olmsted Teisberg suggested that the value of healthcare should be measured by treatment outcomes related to costs. Policy should financially reward treatment effects and in an outline of value-based healthcare, they predicted: 1. State control policy yields variable effects, increasing costs 2. Low price policy decreases e...

Diabetes Mellitus is one chronic disease that is still a health problem requiring prolonged treatment, so good family support is needed. This research aims to identify family support for diabetes mellitus type II patients at the primary health centre. The research conducted is by using a quantitative approach. The sampling technique used was a tota...

p>This paper proposes a distributed bundle al-gorithm for task allocation problems for multi-robot sys-tems. Specifically, in the developed formulation of the ve-hicle routing problem with time windows (VRPTW), the robots are assigned to dispatch necessities for the sur-vivors. The utility of each robot is evaluated by the pref-erence index, which...

p>Effective management of multi-intersection traffic signal control (MTSC) is vital for intelligent transportation systems. Multi-agent reinforcement learning (MARL) has shown promise in achieving MTSC. However, existing MARL-based MTSC algorithms have primarily focused on capturing the spatial relationship between multi-intersection traffic signal...

The anterior cingulate cortex (ACC) plays a crucial role in encoding, consolidating and retrieving memories related to emotionally salient experiences, such as aversive and rewarding events. Various studies have highlighted its importance for fear memory processing, but its circuit mechanisms are still poorly understood. Cortical layer 1 (L1) of th...

Psychological flow is a positive experience achieved through a near-balance of task challenge and skill capability, creating a merging of awareness and action and leading to an intrinsically rewarding feeling. Flow has typically been documented in persons who participate in work and leisure activities where they can exercise a large degree of creat...

We consider the reinforcement learning (RL) problem with general utilities which consists in maximizing a function of the state-action occupancy measure. Beyond the standard cumulative reward RL setting, this problem includes as particular cases constrained RL, pure exploration and learning from demonstrations among others. For this problem, we pro...

Path planning is an essential algorithm in any autonomous mobile robot, including agricultural robots. One of the reinforcement learning methods that can be used for mobile robot path planning is the Q-Learning algorithm. However, the conventional Q-learning method explores all possible robot states in order to find the most optimum path. Thus, thi...

There is a noticeable paucity of recently published research on the roles and responsibilities of peer reviewers for international journals. Concurrently, the pool of these peer reviewers is decreasing. Using a narrative research method developed by the author, this study questioned these roles and responsibilities through the author’s assessment i...

Deep generative models for Natural Language data offer a new angle on the problem of graph synthesis: by optimizing differentiable models that directly generate graphs, it is possible to side-step expensive search procedures in the discrete and vast space of possible graphs. We introduce LIC-GAN, an implicit, likelihood-free generative model for sm...

To investigate the issue of multi-entry bus priority at intersections, an intelligent priority control method based on deep reinforcement learning was constructed in the bus network environment. Firstly, a dimension reduction method for the state vector based on the key lane was proposed, which contains characteristic parameters such as the bus sta...

Imitation learning (IL) algorithms often rely on inverse reinforcement learning (IRL) to first learn a reward function from expert demonstrations. However, IRL can suffer from identifiability issues and there is no performance or efficiency guarantee when training with the learned reward function. In this paper, we propose Protagonist Antagonist Gu...

Gene regulatory networks (GRNs) play crucial roles in various cellular processes, including stress response, DNA repair, and the mechanisms involved in complex diseases such as cancer. Biologists are involved in most biological analyses. Thus, quantifying their policies reflected in available biological data can significantly help us to better unde...

Bunching onion as well as onion show great variability in seed yield among cultivars. Understanding the role of floral rewards and attractants to pollinator species is crucial to improving crop seed yield. Nectar sugar concentration is one of the most important factors affecting bee–flower interaction. The objective of this work was to determine th...

Neuroimaging studies have demonstrated the ability to use the brain activity of a group of individuals to forecast the behavior of an independent group. In the current study, we attempted to forecast aggregate choices in a popular restaurant chain. During our functional magnetic resonance imaging (fMRI) study, 22 participants were exposed to 78 pho...

Multi-robot path finding in dynamic environments is a highly challenging classic problem. In the movement process, robots need to avoid collisions with other moving robots while minimizing their travel distance. Previous methods for this problem either continuously replan paths using heuristic search methods to avoid conflicts or choose appropriate...

We study the convergence of several natural policy gradient (NPG) methods in infinite-horizon discounted Markov decision processes with regular policy parametrizations. For a variety of NPGs and reward functions we show that the trajectories in state-action space are solutions of gradient flows with respect to Hessian geometries, based on which we...

p>This paper proposes a distributed bundle al-gorithm for task allocation problems for multi-robot sys-tems. Specifically, in the developed formulation of the ve-hicle routing problem with time windows (VRPTW), the robots are assigned to dispatch necessities for the sur-vivors. The utility of each robot is evaluated by the pref-erence index, which...

Recommending novel content, which expands user horizons by introducing them to new interests, has been shown to improve users' long-term experience on recommendation platforms \cite{chen2021values}. Users however are not constantly looking to explore novel content. It is therefore crucial to understand their novelty-seeking intent and adjust the re...

Much information security research focuses on policies firms could adopt to reduce or eliminate employees' violation behavior. However, current information security policies are based on increasingly outmoded models of compliance behavior. This paper proposes a novel behavioral-based mechanism that offers rewards and punishments to incentivize empl...

p>Effective management of multi-intersection traffic signal control (MTSC) is vital for intelligent transportation systems. Multi-agent reinforcement learning (MARL) has shown promise in achieving MTSC. However, existing MARL-based MTSC algorithms have primarily focused on capturing the spatial relationship between multi-intersection traffic signal...

This paper will explain why it is vital to adopt sustainable business management to successfully manage global success. As we have noticed in the past 20 years the environment of business has been turned upside down as a result of the interaction of globalisation, emerging technologies, and increased transparency. With regard to one particular aspe...

Diffusion models have achieved remarkable results in image generation, and have similarly been used to learn high-performing policies in sequential decision-making tasks. Decision-making diffusion models can be trained on lower-quality data, and then be steered with a reward function to generate near-optimal trajectories. We consider the problem of...

Federated learning (FL) is a technique that involves multiple participants who update their local models with private data and aggregate these models using a central server. Unfortunately, central servers are prone to single-point failures during the aggregation process, which leads to data leakage and other problems. Although many studies have sho...

Construction accidents occur frequently in China because the supervision of safety standards mandated by the government has not had its intended effect. In this paper, the authors propose a model to incentivize the management of safety during construction that involves the government as well as the owners and contractors in the industry. This study...

Motivating and encouraging employees to work is one of the most important tasks of every manager, but only some of them succeed. Motivation is a complex psychological variable that is difficult to see, and it is even more challenging to direct it in the desired direction. Therefore, it is necessary to research and monitor the needs of each employee...

In natural settings, people evaluate complex multi-attribute situations and decide which attribute to request information about. Little is known about how people make this selection and specifically, how they identify individual observations that best predict the value of a multi-attribute situation. Here show that, in a simple task of information...

India's tribal population is a sizeable minority with distinctive cultural identities, traditions, and beliefs. The Indian government has introduced a number of Programmes and schemes to support their socioeconomic development. This Programme aims to provide the tribal population with basic necessities like housing, healthcare, education, and sanit...

Super-rational aspiration induced strategy updating with exit rights has been considered in some previous studies, in which the players adjust strategies in line with their payoffs and aspirations, and they have access to exit the game. However, exit payoffs for exiting players are automatically allocated, which is clearly contrary to reality. In t...

The Talmud is a rich and complex text with a wealth of insights on living a meaningful, productive life. One way to learn from the Talmud is to examine its stories. Another way, which this paper will take, is to study the many aphorisms and maxims found in the Talmud. These sayings offer further guidance on how to achieve a rewarding life. They rem...

Individual differences in obesity, beyond being explained by metabolic and medical complications, are understood by alterations in eating behaviour which underlie psychological processes. From this psychological perspective, studies have identified several potential characteristic features at the psycho-behavioural level that could additionally exp...

Performance management isn’t just a matter of defining and following a process. Instead, it’s above all a lively and intense interaction between the managers and their reports. Skills and technique underlying an effective and satisfying relationship is essential to ensure sustainable results with involved and motivated teams. We propose a role-play...

Two main challenges in Reinforcement Learning (RL) are designing appropriate reward functions and ensuring the safety of the learned policy. To address these challenges, we present a theoretical framework for Inverse Reinforcement Learning (IRL) in constrained Markov decision processes. From a convex-analytic perspective, we extend prior results on...