Soft actuators, as an important part of soft robotics, have attracted significant attention due to their inherent compliance, flexibility and safety. However, low capacity in force and load limits their applications. Prestored elastic energy can impr...
Given the significant cost of alcohol use disorder (AUD), identifying risk factors for alcohol seeking represents a research priority. Prominent addiction theories emphasize the role of motivation in the alcohol seeking process, which has largely bee...
Despite active research on trading systems based on reinforcement learning, the development and performance of research methods require improvements. This study proposes a new action-specialized expert ensemble method consisting of action-specialized...
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...
Neural networks : the official journal of the International Neural Network Society
Jun 16, 2020
Similar to real snakes in nature, the flexible trunks of snake-like robots enhance their movement capabilities and adaptabilities in diverse environments. However, this flexibility corresponds to a complex control task involving highly redundant degr...
Research in Artificial Intelligence (AI) has focused mostly on two extremes: either on small improvements in narrow AI domains, or on universal theoretical frameworks which are often uncomputable, or lack practical implementations. In this paper we a...
Clinical pharmacology and therapeutics
Feb 23, 2020
The availability of multidimensional data together with the development of modern techniques for data analysis represent an exceptional opportunity for clinical pharmacology. Data science-defined in this special issue as the novel approaches to the c...
Metabolic engineering aims to produce chemicals of interest from living organisms, to advance toward greener chemistry. Despite efforts, the research and development process is still long and costly, and efficient computational design tools are requi...
In many reinforcement learning tasks, the goal is to learn a policy to manipulate an agent, whose design is fixed, to maximize some notion of cumulative reward. The design of the agent's physical structure is rarely optimized for the task at hand. In...
Neural networks : the official journal of the International Neural Network Society
Oct 26, 2019
Complementary Learning Systems (CLS) theory suggests that the brain uses a 'neocortical' and a 'hippocampal' learning system to achieve complex behaviour. These two systems are complementary in that the 'neocortical' system relies on slow learning of...