From springschool at rug.nl Tue Dec 3 07:58:50 2019 From: springschool at rug.nl (Spring School, FA) Date: Tue, 3 Dec 2019 13:58:50 +0100 Subject: [ACT-R-users] Groningen Spring School on Cognitive Modeling: March 30 to April 3, 2020 Message-ID: *Fifth Groningen Spring School on Cognitive Modeling* *? ACT-R, Nengo, PRIMs, error-driven learning, and dynamical systems. ?* Date: *March 30 to April 3, 2020 * Location: Groningen, the Netherlands Fee: ? 250 (late fee after February 15 will be ? 300) More information and registration:* www.cognitive-modeling.com/springschool * We are happy to announce the fifth Groningen Spring School on Cognitive Modeling (March 30 to April 3, 2020). This year, the Spring School will again cover four different modeling paradigms: ACT-R, Nengo, PRIMs, and error-driven learning. It thereby offers a unique opportunity to learn the relative strengths and weaknesses of these approaches. Moreover, this year we are offering a lecture series on dynamical systems, which should be interesting for anyone looking into modeling cognitive dynamics at some level of abstraction. We recommend this lecture series as an excellent combination with Nengo, for those interested in neuromorphic computing. The first day will provide an introduction to all five topics. From day two, spring school students will be asked to commit to one topic, for which they will attend lectures as well as tutorials. In addition, students can sign up for a second topic, for which they will attend lectures only. All students are invited to join a series of plenary research talks on the different paradigms. On the first day, spring school students are asked to introduce themselves and their research interests in a poster session. Registration is now open. For more information and registration, please see the website: www.cognitive-modeling.com/springschool Please feel free to forward the information to anyone who might be interested in the Spring School. We are looking forward to welcoming you in Groningen, The Spring School team ______________ *ACT-R* Teachers: Jelmer Borst, Maarten van der Velde, 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 (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. *Error-driven learning* Teachers: Jacolien van Rij and Doroth?e Hoppe (University of Groningen) Error-driven learning (also called discrimination learning) allows to simulate the time course of learning. It is based on the Rescorla-Wagner model (Rescorla & Wagner, 1972) for animal cognition, which assumes that learning is driven by expectation error, instead of behaviorist association (Rescorla, 1988). The equations formulated by Rescorla and Wagner have been used to investigate different aspects of cognition, including language acquisition (e.g., Hsu, Chater, and Vit?nyi, 2011; St. Clair, Monaghan, and Ramscar, 2009), second language learning (Ellis, 2006), and reading of complex words (Baayen et al, 2011). Although error-driven learning can be applied for all domains in cognitive science, in this course we will focus on how it could be used for modeling language processing and language learning. *Dynamical Systems: a Navigation Guide * Teacher: Herbert Jaeger (University of Groningen) This lecture-series gives a broad overview over the zillions of formal models and methods invented by mathematicians and physicists for describing ?dynamical systems?. Here is a list of covered items: Finite-state automata with and without input, deterministic and non-deterministic, probabilistic), hidden Markov models and partially observable Markov decision processes, cellular automata, dynamical Bayesian networks, iterated function systems, ordinary differential equations, stochastic differential equations, delay differential equations, partial differential equations, (neural) field equations, Takens? theorem, the engineering view on ?signals?, describing sequential data by grammars, Chomsky hierarchy, exponential and power-law long-range interactions, attractors, structural stability, bifurcations, phase transitions, topological dynamics, nonautonomous attractor concepts. In the lectures, I try to work out the underlying connecting lines between the ?dots? listed above. -------------- next part -------------- An HTML attachment was scrubbed... URL: From pblouw at uwaterloo.ca Mon Dec 9 16:45:10 2019 From: pblouw at uwaterloo.ca (Peter Blouw) Date: Mon, 9 Dec 2019 16:45:10 -0500 Subject: [ACT-R-users] Call for Applications - 2020 Nengo Summer School Message-ID: [All details about this school can be found online at https://www.nengo.ai/summer-school] The Centre for Theoretical Neuroscience at the University of Waterloo is excited to announce our 7th annual Nengo summer school on large-scale brain modelling and neuromorphic computing. This two-week school will teach participants to use the Nengo simulation package to build state-of-the-art cognitive and neural models to run both in simulation and on neuromorphic hardware. Summer school participants will be given on-site access to Loihi, Intel?s neuromorphic research chip [1], and will learn to run high-level applications on Loihi using Nengo! More generally, Nengo provides users with a versatile and powerful environment for designing cognitive and neural systems, and has been used to build what is currently the world's largest functional brain model, Spaun [2], which includes spiking deep learning, reinforcement learning, adaptive motor control, and cognitive control networks. For a look at a recent summer school, check out this short video: https://goo.gl/4tVUkQ We welcome applications from all interested graduate students, postdocs, professors, and industry professionals with a relevant background. [1] Davies, et al. (2018). Loihi: A neuromorphic manycore processor with on-chip learning. IEEE Micro. Vol. 38 no. 1 pp. 82-99. [ https://ieeexplore.ieee.org/document/8259423] [2] Eliasmith, C., Stewart T. C., Choo X., Bekolay T., DeWolf T., Tang Y., Rasmussen, D. (2012). A large-scale model of the functioning brain. Science. Vol. 338 no. 6111 pp. 1202-1205. DOI: 10.1126/science.1225266. [ http://compneuro.uwaterloo.ca/files/publications/eliasmith.2012.pdf] ***Application Deadline: February 15, 2020*** Format: A combination of tutorials and project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on building neuromorphic applications, modeling neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or providing a proof-of-concept of various neural mechanisms. Hands-on tutorials, work on individual or group projects, and talks from invited faculty members will make up the bulk of day-to-day activities. A project demonstration event will be held on the last day of the school, with prizes for strong projects! Participants will have the opportunity to learn how to: - interface Nengo with various kinds of neuromorphic hardware (e.g. Loihi, SpiNNaker, BrainDrop) - interface Nengo with (spiking and normal) cameras and robotic systems - integrate machine learning methods into biologically oriented models - implement modern nonlinear control methods in neural models - build perceptual, motor, and sophisticated cognitive models using spiking neurons - model anatomical, electrophysiological, cognitive, and behavioural data - use a variety of single cell models within a large-scale model - and much more? Date and Location: June 7th to June 19th, 2020 at the University of Waterloo, Ontario, Canada. Applications: Please visit https://www.nengo.ai/summer-school/, where you can find more information regarding costs, travel, lodging, along with an application form. We ask that you provide a short description of a possible project, and to briefly indicate how this project might make use of the tools and methods that the summer school will be covering, as listed above. If you have any questions about the school or the application process, please contact Peter Blouw (peter.blouw at appliedbrainresearch.com). The school is partially supported by Applied Brain Research, Inc. We look forward to hearing from you! -------------- next part -------------- An HTML attachment was scrubbed... URL: From 18120255 at bjtu.edu.cn Tue Dec 17 06:55:48 2019 From: 18120255 at bjtu.edu.cn (18120255) Date: Tue, 17 Dec 2019 19:55:48 +0800 Subject: [ACT-R-users] =?utf-8?q?About_python_version_on_the_paper_=3Clear?= =?utf-8?q?ning_rapid_and_precise_skill=3E?= Message-ID: An HTML attachment was scrubbed... URL: From 18120255 at bjtu.edu.cn Wed Dec 18 21:10:35 2019 From: 18120255 at bjtu.edu.cn (18120255) Date: Thu, 19 Dec 2019 10:10:35 +0800 Subject: [ACT-R-users] A python version on the controller module Message-ID: An HTML attachment was scrubbed... URL: