Article
Social Sciences, Interdisciplinary
Feng Wang, Wendian Shi
Summary: Work and leisure balance is crucial for people's well-being. This study found that work-to-leisure conflict and work-to-leisure facilitation were negatively correlated with work-leisure balance satisfaction, while leisure-to-work conflict and leisure-to-work facilitation did not significantly impact work-leisure balance satisfaction. Furthermore, boundary control and work-leisure balance self-efficacy positively influenced work-leisure balance satisfaction.
SOCIAL INDICATORS RESEARCH
(2023)
Review
Environmental Studies
Susan M. Schneider, Angela Sanguinetti
Summary: The paper discusses how learning principles can enhance our understanding of behavioral challenges and improve our effectiveness in addressing them, aiming to interest and involve researchers and practitioners in various energy and sustainability specializations.
ENERGY RESEARCH & SOCIAL SCIENCE
(2021)
Article
Biology
Alana Jaskir, Michael J. Frank
Summary: The basal ganglia plays a role in reinforcement learning and decision making, utilizing complex circuitry and dynamic dopamine modulation to achieve this. The OpAL* model highlights the normative advantages of this circuitry, showing how opponent pathways and dopamine modulation enhance learning and decision-making.
Article
Psychology
Mayank Agrawal, Marcelo G. Mattar, Jonathan D. Cohen, Nathaniel D. Daw
Summary: The article provides a rational analysis of the temporal structure of controlled behavior and offers a formal account. It suggests that cognitive fatigue and boredom are phenomenological counterparts of opportunity cost measures, rather than resource depletion. Fatigue reflects the value of offline computation, while boredom signals the value of exploration.
PSYCHOLOGICAL REVIEW
(2022)
Article
Chemistry, Multidisciplinary
Fidel Aznar, Mar Pujol, Ramon Rizo
Summary: This article discusses a macroscopic swarm foraging behavior achieved through deep reinforcement learning, combining basic fuzzy behaviors to control group movement. The study reveals that this macroscopic behavior can robustly and scalably accomplish foraging tasks in previously unseen situations during training.
APPLIED SCIENCES-BASEL
(2021)
Article
Business
Christopher Michaelson
Summary: The research on meaningful work lacks a shared definition, as it is believed to mean different things to different people. This paper provides a normative account of meaningful work, emphasizing that it should be meaningful to oneself and others, as well as independently. It opens up new possibilities for studying self-aggrandizing and harmful work, as well as the distinction between experienced and normative meaningfulness.
JOURNAL OF BUSINESS ETHICS
(2021)
Article
Economics
Jacob Goldin, Daniel Reck
Summary: The study finds that determining optimal policy is impossible without resolving the ambiguity of whether an observed default effect reflects a welfare-relevant preference or a mistake. The optimal policy depends on the resolution, either minimizing nondefault choices or inducing active choice.
REVIEW OF ECONOMICS AND STATISTICS
(2022)
Article
Hospitality, Leisure, Sport & Tourism
Hsiu-Yu Teng
Summary: This study investigates the impact of work-leisure conflict and facilitation on employee well-being, and finds a positive relationship between job and leisure crafting and well-being. The findings provide guidance for human resource practices in the hospitality industry.
INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Shuai Lu, Shuai Han, Wenbo Zhou, Junwei Zhang
Summary: The paper introduces the Recruitment-Imitation Mechanism (RIM) for evolutionary reinforcement learning, which combines the advantages of reinforcement learning, evolutionary algorithms, and imitation learning. RIM outperforms prior methods in continuous control tasks and features a dual-actor and single critic reinforcement learning agent.
INFORMATION SCIENCES
(2021)
Article
Automation & Control Systems
Javier Garcia, Ismael Sagredo
Summary: Deep Reinforcement Learning systems are effective in complex tasks, but their application in safety-critical domains remains dangerous due to adversarial attacks. This paper proposes a novel instance-based defense method by reusing concepts from existing Safe Reinforcement Learning algorithms to identify and prevent adversarial situations.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Multidisciplinary Sciences
Gergely Horvath
Summary: The study experimentally examines the effectiveness of policy interventions in reducing the negative impact of behavioral biases on job search. It compares the effects of reducing search costs and nudging. The results show that reducing search costs increases job search effort and payoffs, while nudging increases reservation wage. Both interventions mitigate the impact of sunk-cost fallacy on reservation wage.
Editorial Material
Computer Science, Artificial Intelligence
David Israel
Summary: There has been a recent flood of important articles with titles variations on the theme of "X is enough" or "Y is all you need." It is important to approach such claims with skepticism and an open mind. One specific claim in an AIJ Position Paper suggests that reward is enough, and the following is a response to that position.
ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Marine
Jiabao Yu, Jiawei Chen, Ying Chen, Zhiguo Zhou, Junwei Duan
Summary: This article introduces a double broad reinforcement learning algorithm based on hindsight experience replay for improving the efficiency and accuracy of collision avoidance decision-making in unmanned surface vehicles. By decoupling target action selection and target Q value calculation, and adopting hindsight experience replay, the algorithm achieved a 31.9 percentage points higher success rate compared to DQN and a 24.4 percentage points higher success rate compared to BRL.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Eiji Uchibe, Kenji Doya
Summary: This paper introduces a model-free imitation learning method called Entropy-Regularized Imitation Learning (ERIL), which combines forward and inverse reinforcement learning under the framework of an entropy-regularized Markov decision process. Experimental results demonstrate that ERIL is more sample-efficient in MuJoCo simulated environments and vision-based tasks.
Review
Computer Science, Artificial Intelligence
Juan Manuel Davila Delgado, Lukumon Oyedele
Summary: This paper aims to consolidate and summarise research knowledge at the intersection of robotics, reinforcement learning, and construction. The study found that reinforcement and imitation learning approaches have not been widely explored in robotics for construction, and the unstructured and dynamic nature of construction poses challenges for these approaches.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Neurosciences
Kevin Lloyd, Peter Dayan
Article
Multidisciplinary Sciences
Rani Moran, Mehdi Keramati, Peter Dayan, Raymond J. Dolan
NATURE COMMUNICATIONS
(2019)
Article
Multidisciplinary Sciences
Marion Rouault, Peter Dayan, Stephen M. Fleming
NATURE COMMUNICATIONS
(2019)
Article
Neurosciences
Amir-Homayoun Javadi, Eva Zita Patai, Eugenia Marin-Garcia, Aaron Margolis, Heng-Ru M. Tan, Dharshan Kumaran, Marko Nardini, Will Penny, Emrah Duzel, Peter Dayan, Hugo J. Spiers
JOURNAL OF COGNITIVE NEUROSCIENCE
(2019)
Article
Neurosciences
Czarina Evangelista, Arne Hantson, Waqqas M. Shams, Anne Almey, Michael Pileggi, Jacques R. Voisard, Vanessa Boulos, Yaman Al-qadri, Brunella V. Gonzalez Cautela, Fei Xiang Zhou, Jesse Duchemin, Andrew Habrich, Noemie Tito, Ramela A. Koumrouyan, Smita Patel, Victoria Lorenc, Collin Gagne, Khaoula El Ouli, Peter Shizgal, Wayne G. Brake
EUROPEAN JOURNAL OF NEUROSCIENCE
(2019)
Article
Biology
Amir-Homayoun Javadi, Eva Zita Patai, Eugenia Marin-Garcia, Aaron Margois, Heng-Ru M. Tan, Dharshan Kumaran, Marko Nardini, Will Penny, Emrah Duzel, Peter Dayan, Hugo J. Spiers
PROCEEDINGS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES
(2019)
Article
Biochemical Research Methods
Amir Dezfouli, Kristi Griffiths, Fabio Ramos, Peter Dayan, Bernard W. Balleine
PLOS COMPUTATIONAL BIOLOGY
(2019)
Article
Biochemical Research Methods
Sanjeevan Ahilan, Rebecca B. Solomon, Yannick-Andre Breton, Kent Conover, Ritwik K. Niyogi, Peter Shizgal, Peter Dayan
PLOS COMPUTATIONAL BIOLOGY
(2019)
Article
Multidisciplinary Sciences
Sijia Zhao, Maria Chait, Fred Dick, Peter Dayan, Shigeto Furukawa, Hsin-I Liao
NATURE COMMUNICATIONS
(2019)
Article
Biochemical Research Methods
Toby Wise, Jochen Michely, Peter Dayan, Raymond J. Dolan
PLOS COMPUTATIONAL BIOLOGY
(2019)
Article
Multidisciplinary Sciences
Hrvoje Stojic, Jacob L. Orquin, Peter Dayan, Raymond J. Dolan, Maarten Speekenbrink
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2020)
Article
Multidisciplinary Sciences
Ivan Trujillo-Pisanty, Kent Conover, Pavel Solis, Daniel Palacios, Peter Shizgal
Article
Behavioral Sciences
Vasilios Pallikaras, Peter Shizgal
Summary: Deep-brain stimulation can provide relief for treatment-resistant depression by restoring the activity of the seeking system and activating dopamine neurons. Recent research suggests that non-dopaminergic neurons may also play a role in the therapeutic effect.
FRONTIERS IN BEHAVIORAL NEUROSCIENCE
(2022)
Article
Neurosciences
Vasilios Pallikaras, Peter Shizgal
Summary: Major depressive disorder is a leading cause of disability and suicide worldwide. Conventional interventions are ineffective in a sub-group of patients with treatment-resistant depression. Deep brain stimulation of the medial forebrain bundle (MFB) has shown promising clinical effects in managing this severe form of depression.
Article
Neurosciences
Czarina Evangelista, Norhan Mehrez, Esthelle Ewusi Boisvert, Wayne G. Brake, Peter Shizgal
Summary: The intensity and cost of rewards have an impact on the priming effect of rewarding electrical brain stimulation, as demonstrated by a novel measurement method. Through modified experimental paradigms, it was found that the priming effect is resilient to the influence of dopamine D2-like receptors. These findings contribute to a new model of brain reward circuitry.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2023)