Neural networks : the official journal of the International Neural Network Society
Mar 14, 2020
Complex network is a general model to represent the interactions within technological, social, information, and biological interaction. Often, the direct detection of the interaction relationship is costly. Thus, network structure reconstruction, the...
Proceedings of the National Academy of Sciences of the United States of America
Nov 22, 2019
Deployment of autonomous vehicles on public roads promises increased efficiency and safety. It requires understanding the intent of human drivers and adapting to their driving styles. Autonomous vehicles must also behave in safe and predictable ways ...
The Science of the total environment
Nov 2, 2019
The complexity and uncertainties affecting drinking water supply systems and threatening hazards require a comprehensive and effective risk assessment to increase the reliability of drinking water safety, especially for small or household systems. Th...
Neural networks : the official journal of the International Neural Network Society
Aug 25, 2019
Deep Reinforcement Learning (RL) demonstrates excellent performance on tasks that can be solved by trained policy. It plays a dominant role among cutting-edge machine learning approaches using multi-layer Neural networks (NNs). At the same time, Deep...
Artificial intelligence in medicine
Jul 23, 2019
In order to gain insight into oligogenic disorders, understanding those involving bi-locus variant combinations appears to be key. In prior work, we showed that features at multiple biological scales can already be used to discriminate among two type...
Science (New York, N.Y.)
Jul 11, 2019
In recent years there have been great strides in artificial intelligence (AI), with games often serving as challenge problems, benchmarks, and milestones for progress. Poker has served for decades as such a challenge problem. Past successes in such b...
Neural networks : the official journal of the International Neural Network Society
Mar 8, 2019
This paper presents a near optimal adaptive event-based sampling scheme for tracking control of an affine nonlinear continuous-time system. A zero-sum game approach is proposed by introducing a novel performance index. The optimal value function, i.e...
IEEE transactions on neural networks and learning systems
Nov 6, 2018
The unprecedented increase in data volume has become a severe challenge for conventional patterns of data mining and learning systems tasked with handling big data. The recently introduced Spark platform is a new processing method for big data analys...
Evolutionary computation
Jun 22, 2018
Algorithms that learn through environmental interaction and delayed rewards, or reinforcement learning (RL), increasingly face the challenge of scaling to dynamic, high-dimensional, and partially observable environments. Significant attention is bein...
Journal of neural engineering
Feb 22, 2017
OBJECTIVE: We present the first generic theoretical formulation of the co-adaptive learning problem and give a simple example of two interacting linear learning systems, a human and a machine.