The Role of Imagination in Social Scientific Discovery: Why Machine Discoverers Will Need Imagination Algorithms

When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from such activity? A close look at the methodology of interpretive social science reveals several abilities necessary to make a social scientific discovery, and one capacity necessary to possess any of them is imagination. For machines to make discoveries in social science, therefore, they must possess imagination algorithms

Influence of anchoring bias on Bitcoin investors’ trading decisions

Blockchain has been perceived by many professionals as the next revolution of humankind. Its application spreads across multiple industries and aspects of life, but the first impact was to be found in finance. In 2017, cryptocurrency became a new financial phenomenon around the globe when Bitcoin’s value skyrocketed to the peak of $19.535. Many investors, both professional and amateur, have taken part in this modern trend of trading. Unfortunately, a number of those experienced losses due to various reasons. Among which a prominent heuristic called “anchoring” might be one of the causes of incorrect assessment leading to potential damages. Several studies in the past have validated the existence of anchoring bias in conventional stock market. However, current literature failed to address similar effect in cryptocurrency market. This thesis examines the presence of Bitcoin price anchoring in trading decisions of investors. Order dataset, including bids and asks, were collected from Kraken exchange to serve the analysis purpose. The analysis has confirmed that investors’ trading decisions anchored to changes in Bitcoin market price. Furthermore, the result tells that anchoring bias influenced investors’ valuation of price differently when they placed bid or ask orders. Nonetheless, its impact does not vary between bull and bear market situations. In conclusion, investors should be well aware of anchoring bias when making trading decisions. The heuristic can lead to both negative and positive consequences, depending on investor’s perception toward it

Reinforcement Learning: A Survey

This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of current work are summarized. Reinforcement learning is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. The work described here has a resemblance to work in psychology, but differs considerably in the details and in the use of the word ``reinforcement.'' The paper discusses central issues of reinforcement learning, including trading off exploration and exploitation, establishing the foundations of the field via Markov decision theory, learning from delayed reinforcement, constructing empirical models to accelerate learning, making use of generalization and hierarchy, and coping with hidden state. It concludes with a survey of some implemented systems and an assessment of the practical utility of current methods for reinforcement learning.Comment: See http://www.jair.org/ for any accompanying file

GenderMag: A Method for Evaluating Software’s Gender Inclusiveness

In recent years, research into gender differences has established that individual differences in how people problem-solve often cluster by gender. Research also shows that these differences have direct implications for software that aims to support users’ problem-solving activities, and that much of this software is more supportive of problem-solving processes favored (statistically) more by males than by females. However, there is almost no work considering how software practitioners—such as User Experience (UX) professionals or software developers—can find gender-inclusiveness issues like these in their software. To address this gap, we devised the GenderMag method for evaluating problem-solving software from a gender-inclusiveness perspective. The method includes a set of faceted personas that bring five facets of gender difference research to life, and embeds use of the personas into a concrete process through a gender-specialized Cognitive Walkthrough. Our empirical results show that a variety of practitioners who design software—without needing any background in gender research—were able to use the GenderMag method to find gender-inclusiveness issues in problem-solving software. Our results also show that the issues the practitioners found were real and fixable. This work is the first systematic method to find gender-inclusiveness issues in software, so that practitioners can design and produce problem-solving software that is more usable by everyone

Computer Science Principles with Java

This textbook is intended to be used for a first course in computer science, such as the College Board’s Advanced Placement course known as AP Computer Science Principles (CSP). This book includes all the topics on the CSP exam, plus some additional topics. It takes a breadth-first approach, with an emphasis on the principles which form the foundation for hardware and software. No prior experience with programming should be required to use this book. This version of the book uses the Java programming language.https://rdw.rowan.edu/oer/1018/thumbnail.jp

Specification and Performance Optimisation of Real-time Trading Strategies for Betting Exchange Platforms

Since their introduction in June 2000, betting exchanges have revolutionised the nature and practice of betting. Betting exchange markets share some similarities with financial markets in terms of their operation. However, in stark contrast to financial markets, there are very few quantitative analysis tools available to support the development of automated betting exchange trading strategies. This thesis confronts challenges related to the generic specification, back-testing, optimisation and execution of parameterised automated trading strategies for betting exchange markets, and presents a related framework called SPORTSBET. The framework is built on an open-source event-driven platform called URBI, which, to date, has been mainly used to develop applications in the domains of robotics and artificial intelligence. SPORTSBET consists of three main components, each of which addresses a hitherto-unmet research challenge. The first is UBEL, a novel generic betting strategy specification language based on the event-driven scripting language of URBI, which can be used to specify parameterised betting strategies for markets related to a wide range of sports. The second is a complex event processor which is capable of synchronising multiple data streams and either replaying them on an historical basis with dynamic market re-construction, in order to quantify strategy performance, or executing them in real time with either real or virtual capital. The final component is an optimisation platform whereby strategy parameters are automatically refined using a stochastic search heuristic in order to improve strategy performance. Explicitly, the optimisation process involves stochastic initialisation, intermediate stochastic selection and acceptance of the candidate solution. To demonstrate the applicability and effectiveness of SPORTSBET, case studies are presented for betting strategies for a range of sports. As illustrated in the case studies, the SPORTSBET optimisation platform implements Walk-Forward Analysis for the robust parameterisation of betting exchange trading strategies without overfitting. Nonetheless, the outcomes should be carefully interpreted, while numerous tests of a strategy are recommended.Open Acces