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Found 7 papers, 0 papers with code
A biologically inspired computational trust model for open multi-agent systems which is resilient to trustor population changes
We ran a series of simulations to compare CA model to FIRE, a well-established, decentralized trust and reputation model for open MAS under conditions of continuous trustee and trustor population replacement, as well as continuous change of trustees' abilities to perform tasks.
Using machine learning techniques to predict hospital admission at the emergency department
Introduction: One of the most important tasks in the Emergency Department (ED) is to promptly identify the patients who will benefit from hospital admission.
Pulmonary embolism identification in computerized tomography pulmonary angiography scans with deep learning technologies in COVID-19 patients
In this study, we present some of the most accurate and fast deep learning models for pulmonary embolism identification in CTPA-Scans images, through classification and localization (object detection) approaches for patients infected by COVID-19.
How game complexity affects the playing behavior of synthetic agents
Agent based simulation of social organizations, via the investigation of agents' training and learning tactics and strategies, has been inspired by the ability of humans to learn from social environments which are rich in agents, interactions and partial or hidden information.
Decision Trees for Helpdesk Advisor Graphs
We use decision trees to build a helpdesk agent reference network to facilitate the on-the-job advising of junior or less experienced staff on how to better address telecommunication customer fault reports.
On Using Linear Diophantine Equations to Tune the extent of Look Ahead while Hiding Decision Tree Rules
This paper focuses on preserving the privacy of sensitive pat-terns when inducing decision trees.
Data set operations to hide decision tree rules
This paper focuses on preserving the privacy of sensitive patterns when inducing decision trees.
