Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions.
Central to effective decision-making is the discipline of optimization, which seeks th ...
The ubiquity of distributed machine learning (ML) in sensitive public domain applications calls for algorithms that protect data privacy, while being robust to faults and adversarial behaviors. Although privacy and robustness have been extensively studied ...
Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...
The current approach to train Cardiopulmonary Resuscitation (CPR) is to employ a mannequin device replicating the physical properties of a real human head and torso. This aims to ensure a correct transfer of the cardiac massage location, amplitude and freq ...
In chess, a series of moves is made until a delayed sparse feedback (win, loss) is issued, which makes it impossible to evaluate the value of a single move. There are powerful reinforcement learning (RL) algorithms, which can cope with these sequential dec ...
Among various subjective quality evaluation methodologies, paired comparison has the advantage of improved simplicity of the subjects’ evaluation task due to simplified rating scales and direct comparison of two stimuli. Thus, it may lead to more reliable ...
In this paper, we propose a new integration approach to simulate an autonomous virtual agent's cognitive learning of a task for interactive virtual environment applications. Our research focuses on the behavioural animation of virtual humans capable of act ...
