AIMC Topic: Decision Making

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Intuitionistic Fuzzy Hierarchical Multi-Criteria Decision Making for Evaluating Performances of Low-Carbon Tourism Scenic Spots.

International journal of environmental research and public health
Low-carbon tourism is an effective solution to cope with the goal conflict between developing tourist economy and responding to carbon emission reduction and ecological environment protection. Tourism scenic spots are important carriers of tourist ac...

Ordinal labels in machine learning: a user-centered approach to improve data validity in medical settings.

BMC medical informatics and decision making
BACKGROUND: Despite the vagueness and uncertainty that is intrinsic in any medical act, interpretation and decision (including acts of data reporting and representation of relevant medical conditions), still little research has focused on how to expl...

Evaluation of the COVID-19 Pandemic Intervention Strategies with Hesitant F-AHP.

Journal of healthcare engineering
In this study, a hesitant fuzzy AHP method is presented to help decision makers (DMs), especially policymakers, governors, and physicians, evaluate the importance of intervention strategy alternatives applied by various countries for the COVID-19 pan...

Multi-AI competing and winning against humans in iterated Rock-Paper-Scissors game.

Scientific reports
Predicting and modeling human behavior and finding trends within human decision-making processes is a major problem of social science. Rock Paper Scissors (RPS) is the fundamental strategic question in many game theory problems and real-world competi...

Improving the accuracy of medical diagnosis with causal machine learning.

Nature communications
Machine learning promises to revolutionize clinical decision making and diagnosis. In medical diagnosis a doctor aims to explain a patient's symptoms by determining the diseases causing them. However, existing machine learning approaches to diagnosis...

Risk management system and intelligent decision-making for prefabricated building project under deep learning modified teaching-learning-based optimization.

PloS one
This study establishes a model of prefabricated building project risk management system based on the Modified Teaching-Learning-Based-Optimization (MTLBO) algorithm and a prediction model of deep learning multilayer feedforward neural network (Backpr...

Robotic assessment of rapid motor decision making in children with perinatal stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Activities of daily living frequently require children to make rapid decisions and execute desired motor actions while inhibiting unwanted actions. Children with hemiparetic cerebral palsy due to perinatal stroke may have deficits in exec...

Deep Reinforcement Learning and Its Neuroscientific Implications.

Neuron
The emergence of powerful artificial intelligence (AI) is defining new research directions in neuroscience. To date, this research has focused largely on deep neural networks trained using supervised learning in tasks such as image classification. Ho...