AIMC Topic: Decision Making

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A fully autonomous terrestrial bat-like acoustic robot.

PLoS computational biology
Echolocating bats rely on active sound emission (echolocation) for mapping novel environments and navigating through them. Many theoretical frameworks have been suggested to explain how they do so, but few attempts have been made to build an actual r...

Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.

Journal of diabetes science and technology
In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care. With the creation of new sensors for physiological monitoring sensors and the introduction of smart insulin pens, novel data relationships based on ...

Mental labour.

Nature human behaviour
Mental effort is an elementary notion in our folk psychology and a familiar fixture in everyday introspective experience. However, as an object of scientific study, mental effort has remained rather elusive. Cognitive psychology has provided some too...

Should Artificial Intelligence Augment Medical Decision Making? The Case for an Autonomy Algorithm.

AMA journal of ethics
A significant proportion of elderly and psychiatric patients do not have the capacity to make health care decisions. We suggest that machine learning technologies could be harnessed to integrate data mined from electronic health records (EHRs) and so...

A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User.

Sensors (Basel, Switzerland)
Nowadays, many robotic applications require robots making their own decisions and adapting to different conditions and users. This work presents a biologically inspired decision making system, based on drives, motivations, wellbeing, and self-learnin...

People are averse to machines making moral decisions.

Cognition
Do people want autonomous machines making moral decisions? Nine studies suggest that that the answer is 'no'-in part because machines lack a complete mind. Studies 1-6 find that people are averse to machines making morally-relevant driving, legal, me...

Controlling an organic synthesis robot with machine learning to search for new reactivity.

Nature
The discovery of chemical reactions is an inherently unpredictable and time-consuming process. An attractive alternative is to predict reactivity, although relevant approaches, such as computer-aided reaction design, are still in their infancy. React...

Classification of ADHD with bi-objective optimization.

Journal of biomedical informatics
Attention Deficit Hyperactive Disorder (ADHD) is one of the most common diseases in school aged children. In this paper, we consider using fMRI data with classification techniques to aid the diagnosis of ADHD and propose a bi-objective ADHD classific...

A computer-based approach for data analyzing in hospital's health-care waste management sector by developing an index using consensus-based fuzzy multi-criteria group decision-making models.

International journal of medical informatics
BACKGROUND: Proper Health-Care Waste Management (HCWM) and integrated documentation in this sector of hospitals require analyzing massive data collected by hospital's health experts. This study presented a quantitative software-based index to assess ...

Learning to activate logic rules for textual reasoning.

Neural networks : the official journal of the International Neural Network Society
Most current textual reasoning models cannotlearn human-like reasoning process, and thus lack interpretability and logical accuracy. To help address this issue, we propose a novel reasoning model which learns to activate logic rules explicitly via de...