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The Entropy Mastermind Game as a Tool for Understanding Human and Artificial Intelligence

University of Surrey | Lara Bertram, Eloisa Bentivegna, Jonathan D. Nelson

Beat the computer and become a Mastermind in this game-based session about computational complexity, information theory and thinking in humans and machines.

Human-like computing is a field of research with the aim to apply principles of human cognition, perception and action to the design of efficient computer algorithms. Computers learn from big data and can perform complex computation, while humans learn from few instances and often use computational shortcuts. Yet, the computational power of machines is limited and combinatoric problems may blow up to a point where the computer is not able to solve them anymore. Surprisingly, humans do comparatively well on some of these problems. Thus, equipping computer algorithms with human-like cognitive properties can increase the efficiency of algorithms and save computational resources.

In this event we will play a game, Entropy Mastermind, which is based on the classic Mastermind game. In this game, which confronts you with a computationally complex problem, you have to guess a secret code which was randomly generated from a probability distribution by making queries and getting feedback.

We will discuss strategies to solve the game efficiently and present basic concepts of probabilities and entropy, computational complexity and the differences between human- and machine-like problem solving. From there, we will derive key ideas for the development of efficient algorithms based on a combination of human-like and computer-like computational principles.

PUBLIC GAME SESSION ON ZOOM.

This is a digital event. When the event is taking place, you get access via a link on this site. Add the event to your schedule and receive a reminder.

Suitable for children.

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Lara Bertram

University of Surrey

PhD student in cognitive psychology

Lara Bertram is a second year PhD student in Cognitive Psychology at University of Surrey, UK. She investigates the role of specific emotions in people’s evaluations of probabilistic uncertainty (entropy), information search and game-based digital learning about probabilities. She also studies Computer Science at Free University Berlin and freelances as a moderator in market research.

Eloisa Bentivegna

IBM Research Europe

Research Staff Member at IBM Research Europe

Dr. Eloisa Bentivegna is a research scientist at IBM. Her work involves building computational models of complex physical systems, from gravitation to fluid dynamics to particle physics. Most recently, she has been investigating new approaches to the search, optimization, and problem inversion of large-scale models using physics-aware AI.

Jonathan D. Nelson

University of Surrey

Lecturer in Cognitive Psychology

Jonathan Nelson is a lecturer in experimental cognitive psychology at University of Surrey. He researches the psychology, mathematics, and cognitive neuroscience of uncertainty and information. He also works to use educational games to teach mathematical principles.

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