Environmental Intelligence using Machine Learning Applications

Stock Price Prediction using Machine Learning and Swarm Intelligence

Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...

An Analysis of Machine Learning Intelligence

Deep neural networks (DNNs) have set state of the art results in many machine learning and NLP tasks. However, we do not have a strong understanding of what DNN models learn. In this paper, we examine learning in DNNs through analysis of their outputs. We compare DNN performance directly to a human population, and use characteristics of individual data points such as difficulty to see how well ...

Improving Opponent Intelligence by Machine Learning

Artificially intelligent opponents in virtual world computer games are almost exclusively controlled by manually-designed scripts. With increasing game complexity, the scripts tend to become quite complex too. As a consequence they often contain “holes” that can be exploited by the human player. The research question addressed in this paper reads: How can machine learning be used to improve the...

Developments in computational intelligence and machine learning

Publisher Rights Statement: NOTICE: this is the author’s version of a work that was accepted for publication in Neurocomputing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. ...

Next Generation Artificial Intelligence and Machine Learning