Related papers: Challenge design roadmap
Data Science research is undergoing a revolution fueled by the transformative power of technology, the Internet, and an ever increasing computational capacity. The rate at which sophisticated algorithms can be developed is unprecedented,…
In science as elsewhere, attention is a limited resource and scientists compete with one another to produce the most exciting, novel and impactful results. We develop a game-theoretic model to explore how such competition influences the…
Learning Games (LGs) are educational environments based on a playful approach to learning. Their use has proven to be promising in many domains, but is at present restricted by the time consuming and costly nature of the developing process.…
Awareness of cybersecurity topics, e.g., related to secure coding guidelines, enables software developers to write secure code. This awareness is vital in industrial environments for the products and services in critical infrastructures. In…
A hallmark of human intelligence is the ability to ask rich, creative, and revealing questions. Here we introduce a cognitive model capable of constructing human-like questions. Our approach treats questions as formal programs that, when…
As Machine Learning (ML) systems becomes more ubiquitous, ensuring the fair and equitable application of their underlying algorithms is of paramount importance. We argue that one way to achieve this is to proactively cultivate public…
Curriculum learning--ordering training examples in a sequence to aid machine learning--takes inspiration from human learning, but has not gained widespread acceptance. Static strategies for scoring item difficulty rely on indirect proxy…
People are remarkably capable of generating their own goals, beginning with child's play and continuing into adulthood. Despite considerable empirical and computational work on goals and goal-oriented behavior, models are still far from…
In this competition, participants will address two fundamental causal challenges in machine learning in the context of education using time-series data. The first is to identify the causal relationships between different constructs, where a…
Data competitions rely on real-time leaderboards to rank competitor entries and stimulate algorithm improvement. While such competitions have become quite popular and prevalent, particularly in supervised learning formats, their…
Most scientists are aware that, in addition to the traditional and subscription-based publication model, there is also the possibility of publishing their research in open access. Various surveys show that scientists are in favour of this…
What should I work on first? What can wait until later? Which projects should I prioritize and which tasks are not worth my time? These are challenging questions that many people face every day. People's intuitive strategy is to prioritize…
The ecosystem of artificial intelligence competitions is a diverse and multifaceted landscape, encompassing a variety of platforms that each host numerous competitions annually, alongside a plethora of specialized websites dedicated to…
It is widely accepted that understanding system requirements is important for software development project success. However, this paper presents two novel challenges to the requirements concept. First, where many plausible approaches to…
In an increasingly connected and networked world, the National Aeronautics and Space Administration (NASA) recognizes the value of the public as a strategic partner in addressing some of our most pressing challenges. The agency is working…
Research shows that many of the challenges currently encountered with agile development are related to requirements engineering. Based on design science research, this paper investigates critical challenges that arise in agile development…
Digital technologies are becoming increasingly prevalent in education, enabling personalized, high quality education resources to be accessible by students across the world. Importantly, among these resources are diagnostic questions: the…
Online judges are systems designed for the reliable evaluation of algorithm source code submitted by users, which is next compiled and tested in a homogeneous environment. Online judges are becoming popular in various applications. Thus, we…
Game AI competitions are important to foster research and development on Game AI and AI in general. These competitions supply different challenging problems that can be translated into other contexts, virtual or real. They provide…
Benchmark hacking refers to tuning a machine learning model to score highly on certain evaluation criteria without improving true generalization or faithfully solving the intended problem. We study this phenomenon in a generic machine…