AIMC Topic: Cooperative Behavior

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Competition and Collaboration in Cooperative Coevolution of Elman Recurrent Neural Networks for Time-Series Prediction.

IEEE transactions on neural networks and learning systems
Collaboration enables weak species to survive in an environment where different species compete for limited resources. Cooperative coevolution (CC) is a nature-inspired optimization method that divides a problem into subcomponents and evolves them wh...

HemOnc.org: A Collaborative Online Knowledge Platform for Oncology Professionals.

Journal of oncology practice
PURPOSE: Cancer care involves extensive knowledge about numerous chemotherapy drugs and chemotherapy regimens. This information is constantly evolving, and there has been no freely available, comprehensive, centralized repository of chemotherapy info...

Why is AI Not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling.

IEEE transactions on visualization and computer graphics
This paper explores the potential for human-AI collaboration in the context of data storytelling for data workers. Data storytelling communicates insights and knowledge from data analysis. It plays a vital role in data workers' daily jobs since it bo...

From Cases to Confidence: Developing Diagnostic Reasoning Skills Through Collaborative Learning in Graduate Nursing Education.

Nursing education perspectives
Teaching diagnostic reasoning to graduate nursing students is both essential and challenging, particularly in asynchronous environments where absence of real-time interaction requires innovative strategies to engage students and support the developme...

Equitably Applying Artificial Intelligence in the United States Workforce Using Training and Collaboration.

New solutions : a journal of environmental and occupational health policy : NS
Advances in artificial intelligence (AI) have raised ethical concerns related to fairness, privacy, and trust. While AI may improve elements of the economy, its benefits will be unevenly experienced with more than half of jobs in the United States ex...

Bridging the gap between scientists and clinicians: addressing collaboration challenges in clinical AI integration.

BMC anesthesiology
This article explores challenges for bridging the gap between scientists and healthcare professionals in artifical intelligence (AI) integration. It highlights barriers, the role of interdisciplinary research centers, and the importance of diversity,...

AI and XAI second opinion: the danger of false confirmation in human-AI collaboration.

Journal of medical ethics
Can AI substitute a human physician's second opinion? Recently the published two contrasting views: Kempt and Nagel advocate for using artificial intelligence (AI) for a second opinion except when its conclusions significantly diverge from the initi...

A Semi-Automated Approach Based on Network Analysis to Suggest New Collaborations and Foster Multisite Clinical Trials.

Studies in health technology and informatics
Several research institutions nowadays collaboratively conduct many scientific projects. Within a national Italian initiative on robotic rehabilitation, this study aims to develop new collaborations that can support the project's missions. Bibliograp...

A Dataset for Understanding Radiologist-Artificial Intelligence Collaboration.

Scientific data
This dataset, Collab-CXR, provides a unique resource to study human-AI collaboration in chest X-ray interpretation. We present experimentally generated data from 227 professional radiologists who assessed 324 historical cases under varying informatio...

Evolutionary multi-agent reinforcement learning in group social dilemmas.

Chaos (Woodbury, N.Y.)
Reinforcement learning (RL) is a powerful machine learning technique that has been successfully applied to a wide variety of problems. However, it can be unpredictable and produce suboptimal results in complicated learning environments. This is espec...