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Full-Text Articles in Social and Behavioral Sciences
Structured Reflection Increases Intentions To Reduce Other People’S Health Risks During Covid-19, Jairo Ramos, Marrissa D. Grant, Stephan Dickert, Kimin Eom, Alex Flores, Gabriela M. Jiga-Boy, Tehila Kogut, Marcus Mayorga, Eric J. Pedersen, Beatriz Pereira, Enrico Rubaltelli, K Sherman David, Paul Slovic, Västjäll. Daniel, Leaf Van Boven
Structured Reflection Increases Intentions To Reduce Other People’S Health Risks During Covid-19, Jairo Ramos, Marrissa D. Grant, Stephan Dickert, Kimin Eom, Alex Flores, Gabriela M. Jiga-Boy, Tehila Kogut, Marcus Mayorga, Eric J. Pedersen, Beatriz Pereira, Enrico Rubaltelli, K Sherman David, Paul Slovic, Västjäll. Daniel, Leaf Van Boven
Research Collection School of Social Sciences
People believe they should consider how their behavior might negatively impact other people, Yet their behavior often increases others’ health risks. This creates challenges for managing public health crises like the COVID-19 pandemic. We examined a procedure wherein people reflect on their personal criteria regarding how their behavior impacts others’ health risks. We expected structured reflection to increase people's intentions and decisions to reduce others’ health risks. Structured reflection increases attention to others’ health risks and the correspondence between people's personal criteria and behavioral intentions. In four experiments during COVID-19, people (N = 12,995) reported their personal criteria about how …
Heterogeneous Attentions For Solving Pickup And Delivery Problem Via Deep Reinforcement Learning, Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang
Heterogeneous Attentions For Solving Pickup And Delivery Problem Via Deep Reinforcement Learning, Jingwen Li, Liang Xin, Zhiguang Cao, Andrew Lim, Wen Song, Jie Zhang
Research Collection School Of Computing and Information Systems
Recently, there is an emerging trend to apply deep reinforcement learning to solve the vehicle routing problem (VRP), where a learnt policy governs the selection of next node for visiting. However, existing methods could not handle well the pairing and precedence relationships in the pickup and delivery problem (PDP), which is a representative variant of VRP. To address this challenging issue, we leverage a novel neural network integrated with a heterogeneous attention mechanism to empower the policy in deep reinforcement learning to automatically select the nodes. In particular, the heterogeneous attention mechanism specifically prescribes attentions for each role of the …