Loading Events

Lunch Pitch with Markus Nyberg and Juan Carlos Nieves Sanchez: A game with unexpected death and a question about giving artificial systems common sense.

To promote meetings between researchers from different places or disciplines, IceLab organises interdisciplinary research lunches with the vision to let ideas meet and mate. During the Lunch Pitch Season, the creative lunch meetings take place at KBC every other Tuesday.

Place: KBCon Lilla Fokusrum  (KBC Focus Environment’s glass room), KBC
Time: Tuesday 6 March at 12:00.
Sign up for a free sandwich before Monday 10:00!

First Pitcher:

Markus Nyberg

Markus Nyberg
IceLab (Integrated Science Lab) and Physics Department

A biased coin-tossing game with weird rules and unexpected death – Applicative to living systems?

About Markus: Markus Nyberg is a PhD student in Theoretical Physics working at IceLab since 2014. His research focuses on stochastic processes, particularly first passage dynamics with applications in cell biology.


In this IceLab lunch pitch I am looking for an application in living systems that can explain a weird coin-tossing game.

Consider a coin-tossing game between two players, Ebba and Mimmi. The game ends when the first player has won X number coin-tosses more than the other player. However, there are special rules in this coin-tossing game. First, the coin is not fair, so Ebba will have a higher probability to win each coin toss. Secondly, at the beginning, Mimmi will be Y>0 tosses away from reaching X, so the score is not necessarily ”0-0” from the start. And last, at random tosses, the score is reseted back to what it was at the start the game. The question is: who will win, and how many coin-tosses, on average, are needed to end this weird coin-tossing game?

Using a simple toy model to mimic this weird coin-tossing game, this question can be answered and boiled down to an equation. At the IceLab lunch pitch I will present to you an animation of my toy model, and then you will (hopefully) figure out what problem it can solve, motivating why I am studying this toy model.

Juan Carlos Nieves Sanchez

Second Pitcher:
Juan Carlos Nieves Sanchez
Department of Computing Science

From factual knowledge to defeasible knowledge.

About Juan Carlos: Juan Carlos Nieves Sanchez is a senior researcher at the Department of Computing Science, Umeå University and a member of the User Interaction and Knowledge Modelling Research Group. His focus is on Artificial Intelligence.  His research interests touch on knowledge representation and reasoning, declarative programming, argumentation theory and knowledge-based systems.

One of the main goals of Artificial Intelligence is to characterize intelligent systems that could mimic the reasoning capabilities of humans. In this regard, commonsense reasoning is an expected skill of the so-called intelligent-software systems. Although commonsense reasoning was introduced by John McCarthy around the 1950’s as a premier research area in Artificial Intelligence, there has been no general solution to the commonsense reasoning problem until now. In this pitch, I will highlight the role of defeasible knowledge in the settings of commonsense reasoning and intelligent-software systems. By defeasible knowledge, I mean knowledge that does not always hold true.

Read more on Juan Carlos Nieves Sanchez website

Share This Post