From pblouw at uwaterloo.ca Thu Jan 7 16:59:00 2016 From: pblouw at uwaterloo.ca (Peter Blouw) Date: Thu, 7 Jan 2016 16:59:00 -0500 Subject: [ACT-R-users] Call for Applications - 2016 Nengo Summer School Message-ID: Hello! [All details about this school can be found online at http://www.nengo.ca/summerschool] The Centre for Theoretical Neuroscience at the University of Waterloo is inviting applications for our 3rd annual summer school on large-scale brain modeling. This two-week school will teach participants how to use the Nengo software package to build state-of-the-art cognitive and neural models to run in simulation and on neuromorphic hardware. Nengo has been used to build what is currently the world's largest functional brain model, Spaun [1], and provides users with a versatile and powerful environment for designing cognitive and neural systems to run in simulated and real environments. We welcome applications from all interested graduate students, research associates, postdocs, professors, and industry professionals. No specific training in the use of modeling software is required, but we encourage applications from active researchers with a relevant background in psychology, neuroscience, cognitive science, robotics, neuromorphic engineering, computer science, or a related field. For a look at last year's summer school, check out this short video: https://goo.gl/wy4dNC [1] 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://nengo.ca/publications/spaunsciencepaper] ****Application Deadline: February 15, 2016**** *Format*: A combination of tutorials and project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on testing hypotheses, 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! *Topics Covered*: Participants will have the opportunity to learn how to: - 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 - integrate machine learning methods into biologically oriented models - interface Nengo with various kinds of neuromorphic hardware (e.g. SpiNNaker) - interface Nengo with cameras and robotic systems - implement modern nonlinear control methods in neural models - and much more? *Date and Location*: June 5th to June 17th, 2016 at the University of Waterloo, Ontario, Canada. *Applications*: Please visit http://www.nengo.ca/summerschool, where you can find more information regarding costs, travel, lodging, along with an application form listing required materials. If you have any questions about the school or the application process, please contact Peter Blouw (pblouw at uwaterloo.ca). We look forward to hearing from you! -------------- next part -------------- An HTML attachment was scrubbed... URL: From ja0s at andrew.cmu.edu Thu Jan 14 08:29:15 2016 From: ja0s at andrew.cmu.edu (john) Date: Thu, 14 Jan 2016 08:29:15 -0500 Subject: [ACT-R-users] postdoctoral position Message-ID: <5697A2AB.1020502@andrew.cmu.edu> I am looking for a post-doctoral researcher to work on computational models of dynamic skill acquisition.The central question in this research is how learners bring task relevant knowledge to enable the tuning of a skill while still dealing with the information-processing demands of the task.We are currently pursuing this question in the context of playing a video game but the choice of task is flexible. We are looking for someone with strong computational modeling skills, preferably with ACT-R experience.The position is funded for at least two years.Besides interacting with other researchers in our lab, the individual could take advantage of the rich intellectual environment that Carnegie Mellon offers. The person will play a key role in this project with the goal of making a significant advance in the direction of a realistic model of human task learning. If interested please contact me, ja at cmu.edu -- John R. Anderson Richard King Mellon Professor of Psychology and Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Office: Baker Hall 345D Phone: 412-417-7008 Fax: 412-268-2844 email: ja at cmu.edu URL: http://act.psy.cmu.edu/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From n.a.taatgen at rug.nl Mon Jan 25 03:43:07 2016 From: n.a.taatgen at rug.nl (Niels Taatgen) Date: Mon, 25 Jan 2016 09:43:07 +0100 Subject: [ACT-R-users] Reminder: Groningen Spring School on Cognitive Modeling Message-ID: NOTE: register before January 31 to avoid late fee Groningen Spring School on Cognitive Modeling ? ACT-R, Nengo, PRIMs, & Accumulator Models ? Date: April 4-8, 2016 Location: Groningen, the Netherlands Fee: ? 200 (late fee ?50 after January 31) Registration: www.ai.rug.nl/springschool The Groningen Spring School on Cognitive Modeling will cover four different modeling paradigms: ACT-R, Nengo, PRIMs, and Accumulator models. It thereby offers a unique opportunity to learn the relative strengths and weaknesses of these approaches. Each day will consist of four theory lectures, one on each paradigm. Each modeling paradigm also includes hands-on assignments. Although students are free to chose the number of lectures they attend, we recommend students to sign up for lectures on two of the modeling paradigms, and complete the tutorial units for one of the paradigms. At the end of each day there will be a plenary research talk, to show how these different approaches to modeling are applied. Admission is limited, so register soon! ACT-R Teachers: Jelmer Borst, Hedderik van Rijn, Niels Taatgen (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, and the timing extension to ACT-R. 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: http://www.ai.rug.nl/~niels/actransfer.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. Accumulator Models Teacher: Marieke van Vugt (University of Groningen) Decisions can be described in terms of a process of evidence accumulation, modeled with a drift diffusion mechanism. The advantage of redescribing the behavioral data with an accumulator model is that those can be decomposed into more easily-interpretable cognitive mechanisms such as speed-accuracy trade-off or quality of attention. In this course, you will learn about the basic mechanisms of drift diffusion models and apply it to your own dataset (if you bring one). You will also see some applications of accumulator models in the context of neuroscience and individual differences. ================================================= Niels Taatgen - Professor University of Groningen, Artificial Intelligence web: http://www.ai.rug.nl/~niels email: n.a.taatgen at rug.nl Telephone: +31 50 3636435 Office: Bernoulliborg 322 ================================================= -------------- next part -------------- An HTML attachment was scrubbed... URL: From glenn.gunzelmann at us.af.mil Tue Jan 26 16:49:50 2016 From: glenn.gunzelmann at us.af.mil (GUNZELMANN, GLENN F DR-03 USAF AFMC 711 HPW/RHAC) Date: Tue, 26 Jan 2016 21:49:50 +0000 Subject: [ACT-R-users] Research Positions with the U.S. Air Force Research Laboratory Message-ID: <5CC9CA51959B144AA55D3C7CAF41791B35AEF6E7@52ZHTX-D08-01A.area52.afnoapps.usaf.mil> **With apologies and respect to our valued colleagues of other nationalities, only U.S. citizens and permanent legal residents of the United States are eligible for these positions.** The U.S. Air Force Research Laboratory's Cognitive Models and Agents Branch has a variety of research positions available for talented cognitive, computational, and computer scientists interested in working on basic and applied cognitive science research. Positions will contribute to various projects spanning the breadth research activities within the branch, including: (a) predictive models of learning and forgetting; (b) decision heuristics; (c) interactive task learning; (d) robustness; (e) simulations of fatigue and vigilance; (f) integrated models of physiology, perception, cognition, and action; (g) autonomous teammates and trainers, and (h) high performance and distributed computing for model testing and validation. We have a number of full-time, paid positions available to qualified and enthusiastic individuals, including at least the following: 1. Full-time government civilian employee (early to mid-career): Focus is on the application of computational cognitive science and artificial intelligence to autonomy. See position description and application instructions here: https://www.usajobs.gov/GetJob/ViewDetails/427565200 **Note: The application deadline for this is 1 February!! 2. Model developer (multiple opportunities): PhD required. Experience in developing computational models in complex tasks. Preference for a range of experience encompassing multiple modeling approaches spanning multiple levels of abstraction (e.g., Soar; ACT-R; IMPRINT; GOMS) 3. Software engineer: Background/familiarity with cognitive science and artificial intelligence is a benefit 4. Sleep Scientist: Experience in designing and executing experiments involving 24+ hours of total sleep deprivation 5. Research Assistants (B.S. or B.A. in psychology): Experience in experiment design, data collection, and analysis. Experience with R and/or Matlab desired. Experience with EEG also a plus. Excellent writing & communication skills. All positions are located in Dayton, OH, at Wright Patterson Air Force Base. Positions would start as early as June 2016. If interested, please email Glenn Gunzelmann at glenn.gunzelmann at us.af.mil. Include a current CV. -Glenn ____________________________________ Glenn Gunzelmann, Ph.D. Senior Research Psychologist S&T Advisor, Cognitive Models & Agents Branch 711 HPW/RHAC 2620 Q Street Bldg 852, Rm 3-312 Wright-Patterson AFB, OH 45433-7905 Phone: (937) 938-3554 Email: glenn.gunzelmann at us.af.mil ____________________________________