____________________ Sixth Groningen Spring School on Cognitive Modeling – ACT-R, Nengo, PRIMs – Date: 27-31 March 2023 Location: Groningen, the Netherlands Fee: € 305 (late fee after February 26 will be € 355) More information and registration: www.cognitive-modeling.com/springschool ____________________ Dear colleagues and students, We are excited to announce the sixth Spring School on Cognitive Modeling in Groningen, from 27-31 March 2023! This time, the Spring School will cover three different modeling paradigms: ACT-R, Nengo, and PRIMs. Each of these topics consists of a series of lectures, as well as a number of hands-on exercises (tutorials). Past years have shown that students get most out of the spring school if they really emerge themselves into one modeling paradigm. We therefore recommend you choose one topic for which you will attend both the lectures as well as the tutorials. In addition, you can select a second paradigm, for which you attend the lectures only. To give students a broader picture, there will also be three guest lectures throughout the week. These lectures each give an introduction to yet another modeling paradigm: accumulator models (Leendert van Maanen), error-driven learning models (Jacolien van Rij), and dynamical systems (Herbert Jäger). Everyone is encouraged to attend those lectures. To round of the program, there will be a poster session, where students present themselves and their research, as well as a city tour, and our (in)famous spring school dinner. Registration is now open. Please feel free to forward the information to anyone who might be interested in the Spring School. We are looking forward to welcoming you (again) in Groningen, The Spring School team springschool@rug.nl ______________ ACT-R Teachers: Jelmer Borst, Stephen Jones, & Katja Mehlhorn (University of Groningen) Website: http://act-r.psy.cmu.edu ACT-R is a high-level cognitive theory and simulation system for developing cognitive models for tasks that vary from simple reaction time experiments to driving a car, learning algebra, and air traffic control. ACT-R can be used to develop process models of a task at a symbolic level. Participants will follow a compressed five-day version of the traditional summer school curriculum. We will also cover the connection between ACT-R and fMRI. Nengo Teacher: Terry Stewart and Andreas Stöckel (University of Waterloo) Website: http://www.nengo.ca Nengo is a toolkit for converting high-level cognitive theories into low-level spiking neuron implementations. In this way, aspects of model performance such as response accuracy and reaction times emerge as a consequence of neural parameters such as the neurotransmitter time constants. It has been used to model adaptive motor control, visual attention, serial list memory, reinforcement learning, Tower of Hanoi, and fluid intelligence. Participants will learn to construct these kinds of models, starting with generic tasks like representing values and positions, and ending with full production-like systems. There will also be special emphasis on extracting various forms of data out of a model, such that it can be compared to experimental data. PRIMs Teacher: Niels Taatgen (University of Groningen) Website: https://www.ai.rug.nl/~niels/prims/index.html How do people handle and prioritize multiple tasks? How can we learn something in the context of one task, and partially benefit from it in another task? The goal of PRIMs is to cross the artificial boundary that most cognitive architectures have imposed on themselves by studying single tasks. It has mechanisms to model transfer of cognitive skills, and the competition between multiple goals. In the tutorial we will look at how PRIMs can model phenomena of cognitive transfer and cognitive training, and how multiple goals compete for priority in models of distraction. ______________ — Thomas Tiotto, PhD Candidate, CogniGron - Groningen Cognitive Systems and Materials University of Groningen Nijenborgh 9, 9747 AG Groningen, The Netherlands Email: t.f.tiotto@rug.nl Profile: https://www.rug.nl/staff/t.f.tiotto/ Office: 5161 0318 Sent with Spark