Twenty-Fifth Annual ACT-R Workshop Program 2018
The 25th Annual ACT-R Workshop takes place on July 21, 2018 at the University of Wisconsin in Madison during the 2018 MathPsych/ICCM conference.
9:00am Learning and Transfer in Complex Environments
John R. Anderson
Transfer of Cognitive Skills
Frank Ritter, Farnaz Tehranchi, & Jacob Oury
Using a Model to Predict Learning and Retention in a Large Study of a Complex Task
Christian Lebiere & Edward Cranford
Decision Making in the Presence of Deceptive Signals
10:40am Neural and Perceptual Embodiments
John Lindstedt & Michael Byrne
Simple Agglomerative Visual Grouping for ACT-R
Patrick Rice & Andrea Stocco
Using TMS to Test the Associations between ACT-R Modules and Cortical Regions
Andrea Stocco
ACT-R Parameters from Resting State Neuroimaging Data
1:30pm Human Machine Interaction
Gregory Trafton
Two Models of Social Influence
Sterling Somers
CogXAI: Cognitively eXplainable Artificial Intelligence
Nele Russwinkel
Developing a Concept of an Active Self through Natural Interaction
3:10pm Future of ACT-R
Dan Bothell
Software Updates
Everyone
Open Discussion
Mar 24
A one-day ACT-R Workshop took place at University College London on July 26, 2017.
The purpose of the workshop is to discuss issues of interest to the ACT-R community, including but not limited to new architectural modifications and developments, modeling and methodology discussions, scaling and efficiency issues, and ideas for applications and expansion.
2017 ACT-R Workshop Schedule
9:00 – 9:30 Registration
9:30 – 11:00 Big Data Session
Robert L. West New Data Sources: Apps, Online Games, and Literature
Matthew Kelly Using Distributional Semantics Techniques with ACT-R to Handle Corpora and Other Large Datasets
David Reitter Cracking Language with ACT-R: The Case for Big Data
11:00 – 12:30 Open Learning Session
Chris Dancy Project Malmo as a Cognitive Modeling Environment
Bill Kennedy Learning Political Bias with Exposure to Fake News
Ion Juvina Modeling Core Affect in ACT-R
12:30 – 1:30 Lunch
1:30 – 3:30 Future Goals Session
John Anderson Video Games Require a Metacognitive Module
Christian Lebiere A Standard Model of the Mind
Dario Salvucci Expanding the Reach of Cognitive Architectures
Niels Taatgen Maybe 640k Is Not Good Enough Anymore: How To Take ACT-R to the Next Level?
3:30 – 4:00 Coffee Break
4:00 – 6:00 Future of ACT-R Session
Dan Bothell ACT-R Updates
Everyone Open-Ended Discussion
Mar 29
ACT-R 2016 Post-Graduate Summer School
John R. Anderson and Christian Lebiere
Psychology Department, Carnegie Mellon University
Attendees of the 2016 ACT-R Post-Graduate Summer School from left to right (and front to back when one directly behind the other): Marc Halbrügge, Niels Taatgen, Robert Thomson, Christopher Stevens, Dan Bothell, Jelmer Borst, Wayne Gray, David Peebles, Michael Martin, David Reitter, Christian Lebiere, John Anderson, Andrea Stocco, Burcu Arslan, Michael Collins, Othalia Larue, Trudy Buwalda, Robert West, Qiong Zhang, Cvetomir Dimov, Bella Veksler, Troy Kelley, Glenn Gunzelmann, Matthew Kelly, Kevin Gluck, Ion Juvina, Farnaz Tehranchi, Vladislav Veksler, Frank Ritter, Cleotilde Gonzalez, Lael Schooler, Bill Kennedy, Harmen de Weerd.
The 2016 ACT-R Post Graduate Summer School took place from August 7 to 9, 2016 at the Cork Factory Hotel in Lancaster, Pennsylvania. Abstracts from the talks are provided below, and the slides from many are linked from the title.
Jelmer Borst (Groningen) – ACT-R and Neuroscience Revisited: What Did We Learn from EEG and MEG?
Since the early 2000s, we have been using fMRI as a means of informing ACT-R models. As a direct result, the imaginal buffer was introduced to the architecture. After the mapping between ACT-R modules and brain regions became more established, fMRI could also be used as a means of testing and constraining ACT-R models, in some cases requiring a significant redevelopment of models. The drawback of fMRI is its low temporal resolution. To approach the level of temporal detail of ACT-R operations, we have recently turned to EEG and MEG, which provide data at a millisecond-resolution. These experiments have provided evidence for additional processes in the standard fan-experiment: a familiarity process and a more involved decision process. In this talk I will discuss whether these results should lead to changes to the architecture or only to updates of existing models.
Daniel Cassenti (ARL) – Evoked Response Potential Latency Modeling and Production Time Prediction
Although a cognitive process is typically a long sequence of cognitive events (e.g., the sequence of productions in ACT-R), cognitive scientists must infer mental steps based largely on the end points of the process – the stimulus and response. This presentation will examine the relationship between Evoked Response Potentials (ERPs) and the cognitive events they signify, using empirical data to segment between the start and end of a cognitive process. Further, I will examine how to implement these ideas into ACT-R by describing three models. With the successful inclusion of brain localization in ACT-R, this presentation will lay out the case for why it is important to incorporate temporal properties of brain events as well. A program of research is proposed to help improve production time estimation in ACT-R.
Andrea Stocco (Washington) – Implications from a Dynamic Causal Modeling Analysis of Brain Data
In the canonical association between modules and brain regions, ACT-R’s procedural module has been mapped to the basal ganglia. This mapping has found a number of experimental verifications with fMRI, and two neural network models have been put forward that provide a robust biological justification for it. There are two potential problems with this. First, the procedural module makes specific and detailed predictions about the directionality of production rules, which have not been tested against fMRI data. The second problem is that the basal ganglia can only perform a subset of the functions of the procedural module. In this presentation, I will try to address these problems by showing a different way of analyzing fMRI data that provides information about the directionality of variable transfer as well as the demand functions of a module. I will then compare the predictions of ACT-R’s procedural module with the results of this analysis, and use the parts where the model predictions do not match to suggest either modified mappings or perhaps simple modifications to the procedural module.
Kevin Gluck (AFRL) – Pace, Persistence, and Scale
I will describe priorities for the future of the architecture as “Pace, Persistence, and Scale.” I will comment on the extent to which there is any progress on these fronts, describe some enduring challenges, and discuss how these considerations relate to issues of robotic autonomy.
Cleotilde Gonzalez (CMU) – Reflections on Unresolved Problems for Cognitive Architectures
The cognitive mechanisms integrated in ACT-R continue to provide robust demonstrations of computational representations of human behavior. In many ways, this is good news: the essence of human behavior across many environments is alike. However, most of our efforts have focused on demonstrating how the existent mechanisms can account for traditional phenomena rather than on developing new mechanisms to address new classes of phenomena. I will reflect on some open problems in the hope of motivating a discussion of how to represent them computationally.
Dan Bothell (CMU) – Changes and updates for the ACT-R Software
I will describe updates to the current software covering both architectural and functional changes. The most notable architectural change is a new option for the credit assignment of rewards provided in the utility learning mechanism. The change is to only apply rewards to the productions that have “completed” all of their actions instead of to all those which have been selected. The most significant change to the functionality is a redesign of the history tools available in the ACT-R Environment to provide a more uniform interface and a way to save that information for later inspection.
Glenn Gunzelmann (AFRL) – The Fatigue Module: Unusual, but Necessary
The focus of this talk will be on a fatigue module that provides the capacity for fluctuations in performance as a function of sleep loss, circadian rhythms, and time on task. The module is unusual relative to other ACT-R modules for several reasons: it has no buffers and is not directly responsible for the information processing capacity of the architecture, it influences parameters in other modules through direct module-to-module connections that are not moderated by central cognition, and is fundamentally about the limitations of human cognition. These features, though unusual, are consistent with the existing literature on fatigue, and add an essential dimension often lacking in computational theories of human cognition but necessary to achieve the vision of unified theories of cognition.
Ion Juvina (Wright St) – Learning to Trust and Trusting to Learn
In a series of related projects, we study how trust mediates learning and how trust itself is learned during strategic interaction. We describe an ACT-R model of trust dynamics that accounts for learning within and between the games Prisoner’s Dilemma and Chicken, and a series of validation studies aimed at expanding the range of conditions and tasks to which the model can be applied, including team-based learning. Our work on improving the original model poses fundamental questions about the architecture such as how models can represent other models and learn to interact with them. Complex interactions between trust and learning can be best studied in a cognitive architecture such as ACT-R, which already includes a variety of learning mechanisms. However, we found that new equations and mechanisms need to be developed to deal with the intricacies of trust development, calibration, and repair, including a trust update equation that provides a unified account for a number of effects from the trust literature.
Bill Kennedy (GMU) – ACT-R+: Including Social and Emotional Cognitive Functionality
ACT-R does not provide an implemented theory of social or emotional cognition, i.e., beyond rational cognition. Humans are particularly good at social cognition, specifically, identifying animate behavior and reading the minds and simulation of other agents. These capabilities have been localized in the brain, but that functionality is not yet provided within ACT-R. While the architecture includes a very effective model of memory including similarity and priming effects, these capabilities do not include the effect of emotional valence on memory, necessary to explain the experimental findings. This talk will describe these additional capabilities within ACT-R and their application to human phenomena.
Othalia Larue (Wright St) – From Implicit Affect to Explicit Emotion
We propose a new architectural mechanism to be used for modeling affective states in ACT-R. Some of the existing approaches to modeling affect are inspired by appraisal theories and tend to focus on explicit representations that are hardwired rather than learned. Other approaches attempt to touch upon the implicit aspects of affective processes by investigating the physiological correlates of affect. We propose a solution inspired by the core affect theory, which places implicit visceral reactions to sensory stimuli along two continuous dimensions of affect: arousal (intensity) and valence. We translate the two dimensions in ACT-R as activation and valuation, respectively. The proposed approach unifies the emotion and cognition theories by naturally integrating affect into the existing ACTR mechanisms without requiring additional modules or a major reorganization of the architecture.
Nele Russwinkle (Technical University Berlin) – Spatial Module and Mental Rotation
We extended the architecture with a spatial module and modeled learning and the influence of familiar objects in a mental rotation task. The aim is to predict behavior of people in applied task that depend on spatial competence. What kind of technical support would help them with task, when are errors most probable, in what situation is that task too difficult and the user needs further information.
Troy Kelley (ARL) – Episodic Memory Consolidations: Lessons Learned from a Dreaming Robot
As part of the development of the Symbolic and Sub-symbolic Robotics Intelligence System (SS-RICS) we have implemented a memory store to allow a robot to retain knowledge from previous experiences. As part of the development of the event memory store, justification for an off-line, unconscious memory process was tested. Three strategies for the recognition of previous events were compared. We found that the best strategy used a post-processing process for all memories using pruning, abstraction, and cueing. Pruning removed memories, abstraction used categories to reduce metric information and the cueing process provided pointers for the recognition of episodes. Additionally, we found that post-processing memories for retrieval as a parallel process was the most efficient strategy. This presentation will review the lessons learned from this work and discuss the implications for cognitive architectures.
Matthew Kelly (Carleton) – Holographic Declarative Memory: A Scalable Memory Module
We present Holographic Declarative Memory (HDM), a module that replaces the slot-value strings of ACT-R’s declarative memory with holographic vectors. HDM reproduces the functionality of DM using vectors as symbols, which confers advantages when dealing with large databases. We have demonstrated the suitability of HDM as a substitute for DM on variants of the fan effect task. In HDM, association strengths emerge from the geometries of the vector space. HDM is also scalable: HDM is based on previous holographic models that have been used to infer the semantics of concepts from large untagged corpuses. Finally, HDM have been used in neurally plausible cognitive architectures.
Michael K. Martin, Christian Lebiere, MaryAnne Fields & Craig Lennon (CMU) – Learning Category Instances and Feature Utilities in a Feature-Selection Model
We describe a Feature-Selection model that combines the instance-based learning paradigm (to categorize objects defined by configurations of features) with production utility learning (to learn a subset of features relevant to the categorization). The model is intended to eventually serve as a general model that helps anchor perceptual labels in autonomous systems. Although feature selection and categorization are often addressed separately in machine learning projects, they can be integrated in a cognitive architecture such as ACT-R as a combination of mechanisms including blending, flexible chunk types and and reinforcement learning. We will discuss architectural issues including controlling the feedback loop between declarative and procedural memory, adjusting the level of noise with experience, learning across module boundaries, and accuracy-efficiency tradeoffs.
Frank E. Ritter (Penn State) – Modeling Novice to Expert Performance with a Modeling Compiler
In this talk I will present high-level behavior representation languages in general and one in particular (called Herbal) that helps model performance on a spreadsheet task. The task takes novices about 25 minutes to perform and experts about 18. We created a tool to author models from a hierarchical task analysis. The tool creates 12 models, a completely novice model that has to proceduralize everything, and then 11 levels of initial expertise, ranging from basically a novice to someone that can do the task using just procedures. The models predict the novice to expert transition, and were created particularly quickly. The models fit the data surprisingly well, which suggests that we can now model novices and their learning using a GOMS-like model, and that behavioral modeling languages should be used more.
Niels Taatgen (Groningen) – Towards Persistent Cognition
The true potential of cognitive architectures is to generalize over multiple tasks and domains of cognition. However, research in cognitive architectures mainly consists of building models of particular experimental tasks, and therefore has many of the limitations of standard cognitive psychology research that were lamented in Newell’s 20 questions paper. In order to achieve a truly integrated cognitive theory, a number of additional pieces of theory are necessary. The first is knowledge transfer: how can procedural and declarative knowledge be used for more than one task? With PRIMs, I have implemented a set of mechanisms for procedural transfer between tasks. However, this is only a first step towards an architecture that can contain knowledge of many different tasks, and that is capable of learning additional tasks by itself. For this we need mechanisms that are able to specify and prioritize goals, and mechanisms that can learn new tasks from examples, instruction or exploration.
Dan Veksler (ARL) – Simple Task-Actor Protocol: Model Reuse Across Tasks, Task Reuse Across Models
One of the benefits of employing computational process models in Cognitive Science is that such models can perform the same tasks as human participants. Unfortunately, task interfaces do not often lend themselves to be easily parsed by computational models and agents. Even task software written specifically for the purposes of behavioral simulations is often limited in that it is tailored for a specific modeling framework, making it difficult to do cross-framework model comparison. Simple Task-Actor Protocol (STAP) is a basis for task-development methodology that makes psychological experiment software easier to develop, to connect to computational models, and to set up for data logging and playback. STAP-compliant task development enables model-code reuse across tasks, and task reuse across models.
David Peebles (Huddersfield) – Methods for accelerating ACT-R model parameter optimisation
I describe two methods for ACT-R model parameter optimisation that allow the search of a multidimensional parameter space using populations of models. The first, differential evolution, is a simple, general purpose algorithm that employs an iterative process of mutation, recombination and selection on a population of candidate solutions to converge on a global optimum. The second method employs HTCondor, an open source, cross-platform software system designed to enable high throughput computing on networked computers. HTCondor facilitates parameter search by allowing modellers to run large numbers of instances of the same model in parallel. I will describe the basic principles of differential evolution and HTCondor and draw upon my experience with both to demonstrate how they can be used to accelerate the development of ACT-R models.
Lael J. Schooler (Syracuse) – Cognitive Costs of Decision Making Strategies: A Componential Analysis
Several theories of decision making contend that the use of decision strategies can be determined by the mental effort required. But how to measure the effort—or cognitive costs—associated with a strategy? Previous analyses have mainly focused on the number of attributes used and the type of information aggregation. We propose an approach based on the ACT-R cognitive architecture, called the Resource Demand Decomposition Analysis, that quantifies the time costs of strategies for using specific underlying cognitive resources and takes into account interactions between processing operations as well as the possibility of parallel processing. Using this approach, we quantify, decompose, and compare the time costs of two prominent decision strategies, take-the-best (TTB) and tallying (TALLY). Our results show that claims about the “simplicity” of decision strategies need to consider not only the amount of information processed but also the cognitive system in which the strategy is embedded.
Dan Veksler (ARL) – How Persuasive is a Good Fit of Model to Data: Model Flexibility Analysis
A good fit of model predictions to empirical data is often used as an argument for model validity. However, if the model is flexible enough to fit a large proportion of potential empirical outcomes, a good fit becomes less meaningful. Model Flexibility Analysis (MFA) is a method for estimating the proportion of potential empirical outcomes that the model can fit. MFA aids model evaluation by providing a metric for gauging the persuasiveness of a given fit. MFA is more informative than merely discounting the fit by the number of free parameters in the model, as the number of free parameters does not necessarily correlate with the flexibility of the model. We contrast MFA with other flexibility assessment techniques, provide examples of how MFA can help to inform modeling results, and discuss a variety of issues relating to the use, disuse, and misuse of MFA in model validation.
Robert West (Carleton) – Using Macro Architectures to Scale Up to Real World Tasks
Scaling up cognitive models for application to real world sociotechnical systems presents several challenges. The first is that building these models from scratch is prohibitively time consuming. The second is that there are different ways to build models of the same task; the more complex the task, the more different ways there are to model it. The idea of a macro cognitive architecture is based on the claim that people tend to use their micro cognitive architecture (e.g., ACT-R) in consistent ways to solve high-level problems that occur across tasks, including problem solving, navigation, competition, negotiation, and planning. SGOMS is a macro cognitive architecture for modeling how people use expert knowledge in multi-agent, dynamic environments with interruptions and re-planning. It is implemented in ACT-R and provides a template for quickly adding task-specific knowledge to create a complex model. Thus it solves two problems: how to jump-start a complex model and how to deal with specific high-level macro cognitive issues. This talk discusses some of the issues and lessons learned in creating and testing SGOMS and how we might develop a suite of ACT-R-based macro cognitive architectures.
Jan 13
Students and instructors at the 2015 ACT-R Summer School
(L to R) Misha Pavel, Jakub Dotlacil, Lyle Long, Dan Bothell, Michael Collins, Rachel Lerch, Cvetomir Dimov, James McKanna, Cristobal De La Maza, Emmanouil Konstantinidis, John Anderson, Jelmer Borst, Jason Harman, Hassen Gharbi, Daniel Roberts, Othalia Larue, Christian Lebiere, Rebecca Albrecht, Alex Yahja, Jessie Chin, Palvi Aggarwal, Xiaonan Liu, Wai-Tat Fu
Twenty-Second Anuual ACT-R Workshop Program 2015
The 22nd Annual ACT-R Workshop occurred on July 17-19, 2015 at Carnegie Mellon University.
The progam/proceedings are located below.
Friday, July 17
John R. Anderson & Caitlin S. Tenison
Stages of Learning as Revealed by ACT-R Modeling of fMRI Data
J. Gregory Trafton & Anthony M. Harrison
Embodied Gesture and Language
Michael Martin
Exploiting Cognitive Context in Autonomous Perception
Christian Lebiere
Structural Pattern Matching
Anthony M. Harrison
Scaling Up, Scaling Out, and Scaling Understanding
Frank E. Ritter
Comments on documenting models based on documenting an ACT-R compiler
Dario D. Salvucci
ACT-R as Embedded Code
Niels Taatgen
Mobile Models
Panel Discussion
Model-Task Interfacing: General, Scalable Protocols
Vadislav D. Veksler, Ryan M. Hope, Anthony M. Harrison, and Don Morrison
Invited Speaker
Ken ForbusTowards Software Social Organisms: The Companion Architecture
Saturday, July 18
Christopher L. Dancy
Using MindModeling to explore a parameter space and model the effects of circadian rhythms on cognition
Michael Collins, Ion Juvina, & Kevin Gluck
Comparing Predicted and Observed Trust Dynamics Within and Between Games of Strategic Interaction
Lyle N. Long
Modeling Emotion and Temperament on Cognitive Mobile Robots
Alessandro Oltramari
Understanding consumer experience with ACT-R
Rebecca Albrecht, Holger Schultheis, & Wai-Tat Fu
Memory Processing and the Visual Impedance Effect
Michael D. Byrne
Comparing vector-based and ACT-R memory models using large-scale datasets: User-customized hashtag and tag prediction on Twitter and StackOverflow
Jung Aa Moon
Modeling Science Inquiry Skills in an Interactive Simulation Task
Matthew M. Walsh
Spacing effects across multiple re-learning sessions
Panel Discussion
Scaling Up Cognitive Modeling
Christian Lebiere, Michael D. Byrne, Susan Chipman, Dario D. Salvucci, Niels Taatgen, and J. Gregory Trafton
Tutorials and Demos
Niels Taatgen
PRIMs/ACTransfer tutorial
Anthony M. Harrison
Model Development within jACT-R
Franklin P. Tamborello
ACT-Concurrently: Concurrency Work-Around for ACT-R
Vadislav D. Veksler
Standard Task-Actor Protocol: Less code to serve more types of models and human participants
Sunday, July 19
Dan Bothell
Recent Updates to ACT-R
Panel Discussion
Social-network behavior emerges from individuals: Scaling up cognitive representations, experimental infrastructure and cognitive technologies
Cleotilde Gonzalez, Ion Juvina, Christian Lebiere, and Alex Yahja
Jul 21
ACT-R Workshop 2014 at CogSci
Session 1 – Metacognition and Learning
Coty Gonzalez Instance-Based Learning Models of Choice
Stefan Wierda Modeling Theory of Mind in ACTransfer
Niels Taatgen Towards a Model of Life-Long Learning
Session 2 – Embodiment and Interaction
Nick Wilson Habituated Activation: Considerations and Initial Implementation within the SS-RICS Cognitive
Robotics System
Bill Kennedy Social Cognition: ACT-R Models Talking to Each Other
Dario Salvucci From Circles to Cities: Driver Distraction in Traffic
Session 3 – Architecture I
Greg Trafton A Model of Sustained Attention
Rebecca Albrecht Towards a Formal Description of the ACT-R Theory of Cognition with an Application to Spatial
Reasoning
Glenn Gunzelmann Cognitive Moderators: Methodologies for Turning the Fantasy of Unified Theories into Reality
Session 4 – Architecture II
Dan Bothell ACT-R Updates
Robert West ACT-R and the Macro Architecture Hypothesis
John Anderson
Sep 25
ACT-R Workshop 2013 at ICCM
Session 1 – Architecture
Unmesh Kurup Using Expectations to Drive Cognitive Behavior
Niels Taatgen General Strategies for cognitive control
Rob Thomson Bottom-Up Learning: The Case for Associative Memory in ACT-R
Session 2 – Applications
Hugh McLarty Massively Scalable ACT-R
David Reitter Modeling individual differences and need-for-cognition
Mike Schoelles JSON Network Interface to ACT-R
Jerry Vinokurov SAL, a Hybrid Cognitive Architecture, with Applications
Session 3 – Neural
Chris Dancy ACT-RΦ: ACT-R with a physiological substrate
Terry Stewart Neural Python ACT-R
Robert West Is the amygdala a production system?
Session 4 – Future
Dan Bothell ACT-R updates
Jan 20
(L to R) Ioanna Katidioti, Ricky Chng, Yingying Tan, Steven Tenaglia, Daniela Link, Caitlin Tenison, Yanfei Liu, Menno Nijboer, David Tobinski, Jelmer Borst, Dan Bothell, John Anderson, John Lindstedt, Katja Mehlhorn, Sergio Verduzco-Flores, Hanna Fechner, Noam Ben-Asher
Nineteenth Anuual ACT-R Workshop Program 2012
The 19th Annual ACT-R Workshop occurred on July 27, July 28, and July 29, 2012 at Carnegie Mellon University.
The progam/proceedings are located below.
Friday, July 27
fMRI
John Anderson
Presentation: Using fMRI to Discover ACT-R Models
Jelmer Borst
Presentation: Using Model-Based fMRI to Locate the Nerual Correlates of Five ACT-R Modules
Jennifer Ferris-Glick & Heeseung Lee
Presentation: Improving Mathematical Intelligent Tutoring Systems
Yulin Qin, Haiyan Zhou, Zhijian Wang, Jain Yang, Ning Zhong, & John Anderson
Presentation: Intrinsic Neural Connection of ACT-R ROIs
Vision & Robotics
Laura Hiatt, Wallace Lawson, & J. Gregory Trafton
Presentaton: Perception and Reasoning in Cognitive Robotics
Unmesh Kurup
Presentation: Usng Expectation to Drive Cognitive Behavior
Enkhbold Nyamsuren & Niels Taatgen
Presentation: Are There More Red Symbols or Square Symbols? Modeling Peripheral Vision with the PAAV Visual Module
Jerry Vinokurov & Christian Lebiere
Presentation: Unsupervised Learning for Symbol-Grounding in the SAL Hybrid Cognitive Architecture
Games & Strategies
Ion Juvina & Christian Lebiere
Presentaton: Modeling transfer of learning in games of strategic interaction
Matthew Kelly & Robert West
Presentation: Modelling decision-making in prisoner’s dilemma
David Reitter & Christian Lebiere
Presentation: Social Cognition: Memory Decay and Adaptive Information Filtering in an ACT-R Simulation
Matthew Rutledge-Taylor, Robert Thomson, Christian Lebiere, James Staszewski, & John Anderson
Presentation: A Comparison of Rule-Based versus Exemplar-Based Categorization in a Model of Sensemaking
Invited Session
Paul Rosenbloom
Presentaton: Sigma: Towards a Graphical Architecture for Integrated Cognition
Comments & Discussion
Saturday, July 28
Human Computer Interaction
Mike Byrne
Presentation: ACT-R as a Usability Tool for Ballot Design
Jungaa Moon & John Anderson
Presentation: Millisecond Time Interval Esitmation in a Dynamic Task
Sterling Somers & Robert West
Presentation: Macro Cognition: Using SGOMS to Pilot a Flight Simulator
Frank Tamborello
Presentation: ACT-Touch: Multitouch Display Interaction for ACT-R
Memory
Ion Juvina, Michael Qin, & Christian Lebiere
Presentaton: An ACT-R Model fo the N-Back M-Pitch Paradigm
Katja Melhorn, Niels Taatgen, & Fokie Cnossen
Presentation: Previous Experience and Current Context Influence the Generation of Hypotheses from Memory
Darryl Schneider
Presentation: Modeling Speed-Accuracy Tradeoffs in Recognition
Robert Thomson
Presentation: An Updated Implementation of Associative Learning
Knowledge
Jerry Ball
Presentaton: The Need for Language Specific Buffers to Model Binding and Co-Reference in ACT-R/Double-R
Bill Kennedy
Presentation: Modeling the Intutitive Decision Making of One Agent and Tree-Based Decision Making in Thousands
Christian Lebiere
Presentation: Mental Models for Human-Robot Interaction
Alessandro Oltramari
Presentation: ACT-RK: Integrating Mechanism and Knowledge for Visual Intelligence
Dario Salvucci
Presentation: A Large-Scale Knowledge Base for ACT-R
Future
Dan Bothell
Presentaton: New Developments in ACT-R
Panel Discussion
Cognitive Architectures: State, Trends, & Roadmap
Sunday, July 29
Tutorial Introductions
Tutorials
Niels Taatgen
ACTRANSFER
Troy Kelley
SS-RICS
Closing
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Jan 20
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This is a copy of the program materials. Other information is available on the official 2011 PGSS site.
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Program
The PGSS is organized in sessions consisting of extended presentations
and open discussions around a specific theme. Each day features three
90-minute sessions from 9am to 3pm, plus a free-ranging evening commentary
of the topics of the day led by a discussant. The time between the end of
the afternoon session at 3pm and the evening session is set aside for
recreation, dinner, and informal discussions and collaboration. The final
program, with links to the talk slides, appears below.
Sunday, July 17
ACT-R since 2001
Presentation: Dan Bothell
Bottom-up Control
Presentation: Niels Taatgen
Viewpoints: Robert West
Scaling Up: Comprehensiveness, Scale, and Integration
Presentation: Glenn Gunzelmann
Viewpoints: Niels Taatgen, David Reitter
Commentary
Richard Young
Monday, July 18
Memory Systems
Presentation: Christian Lebiere
Viewpoints: Tony Harrison, Jerry Ball, Bill Kennedy
Architecture as Software
Presentation: Frank Ritter
Viewpoints: Coty Gonzalez
Teaching ACT-R
Presentation: Mike Byrne
Viewpoints: Niels Taatgen, Mike Schoelles
Commentary
Dario Salvucci
Tuesday, July 19
Scaling Down: Emotion and Neuroscience
Presentation: Bill Kennedy
Viewpoints: Ion Juvina, Jelmer Borst
Interfacing with Environments and Cognitive Robotics
Presentation: Greg Trafton
Viewpoints: Mike Byrne, Mike Schoelles
The Future of ACT-R
Panel of Organizers
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Jan 20
(L to R) San Hun Lee, Ryan Hope, Hyungseok Oh, Jerry Vinokourov, Yunfeng Zhang, Dan Bothell, David Sloan, John Anderson, Christian Lebiere, Mary Freiman, Chris Bogart, Hee Seung Lee, Daniel Gartenberg, Michelle Moon
ACT-R 2010 Workshop Schedule
Dan Bothell What's new in ACT-R 6.0
Bonnie John CogTool: A Tool for Interface Design and ACT-R Research
Frank Ritter Building Learning Models Quickly that do a Non-iterative Task
David Reitter Hands-on with ACT-UP, a Cognitive Toolbox for Scalable Models
Jelmer Borst Using Cognitive Models to Analyze fMRI Data
Wayne Gray Space Fortress: An Overview
Marc Destefano Modeling Space Fortress: RPI Effort
Dan Bothell Modeling Space Fotress: CMU Effort
Christian Lebiere Softening Representations for Model Reuse and Generality
Dario Salvucci Cognitive Supermodels
John Anderson The Future of ACT-R in the Post-John Era
Jan 20
ACT-R 2009 Workshop Schedule
Opening: ACT-R from CMU's Perspective
John Anderson Overview of ACT-R
Dan Bothell Details of ACT-R 6.0
Presentations 1: Architecture
Christian Lebiere Functional constraints on architectural mechanisms
Leendert van Maanen Retrieval by accumulating evidence in ACT-R
Vladislav D. Veksler A mechanism for decisions in the absence of prior reward
Presentations 2: Extentions
Lael J. Schooler ACT-R forays into the semantic web
Glenn Gunzelmann Making models tired: A module for fatigue
Anthony Harrison Acting outside the box: Truly embodied ACT-R
Michael J. Schoelles Interfacing ACT-R with different types of environments and with different techniques: Issues and suggestions
Panel: Future of ACT-R from a non-CMU Perspective
Danilo Fum
Kevin A. Gluck
Wayne D. Gray
Niels A. Taatgen
J. Gregory Trafton
Richard M. Young
Jan 20
(L to R) Anne Porbadnigk, Neil Jones, Katja Mehlhorn, Carlos Arevalo Mercado, Tiffany Jastrzembski, John Anderson, Niels Taatgen, Atsushi Terao, Darryl Schneider, David Reitter, Dan Bothell, Christian Lebiere, Richard Burns, Edgar Acosta, Rick Moore, Hendrik Neumann
Link to Proceedings
Jan 20
Front Row: (L to R) Niels Taatgen, Christian Lebiere, Michel Brudzinski, John Anderson, Andrea Heiberg, Jack Harris, Yao Hu, Julian Marewski, David Cades, Matthew Walsh, Ion Juvina
Back Row: (L to R) Scott Douglass, Dan Bothell, Fehmida Hussain, Ana Sofia Morais, Kristen Green, Alberto De Obeso Orendain, Sven Bruessow, Varun Dutt
Jan 18
(L to R) Green shirt guy [statue], Paul Kieffaber, Melissa Beck, Orit Hazzan, Amy Santamaria, Brittney Opperman, Barbara Deml, Bella (Zafria) Veksler, Daniel Holt, Melih Gunal, Gustavo Lacerda, Niels Taatgen, John Anderson, Yulin Qin, Dean Petters, Ken McAnally, Dan Bothell, Little red shirt guy [statue], Dad of little red shirt guy [statue], Don Morrison
link to proceedings
All sessions will be in Adamson Wing (room 136A), which is on the first floor of Baker Hall.
Friday
7:45 Continental breakfast
8:15 Welcome
8:30 Five talks (20 minutes each)
John Anderson, A new utility learning mechanism
Perception
Glenn Gunzelmann, Representing Human Spatial Competence in ACT-R
William Kennedy & Greg Trafton, Representing and Reasoning about Space
Greg Trafton, Raj Ratwani & Len Breslow, A Color Perceptual Process Theory: Letting ACT-R see Colors.
Mike Byrne, An ACT-R Timing Module based on the Attentional Gate Model
10:10 Break
10:30 Five talks
Communication and Learning from Instructions
Mike Matessa, Four levels of Communication, Error, and Recovery in ACT-R
Angela Brunstein, Learning Algebra by Exploration
Memory
Leendert van Maanen & Hedderik van Rijn, Memory Structures as User Models
Jong Kim, Frank Ritter & Richard Koubek, Learning and Forgetting in ACT-R.
Jon Fincham & Greg Siegle, Modeling mechanisms that differentiate healthy and depressed individuals: The Paced Auditory Serial Attention Task
12:10 Lunch
1:30-5:30 David Noelle, Leabra tutorial and discussion (with 3:30-4:00 break)
6:30-10:00 Party at the Pittsburgh Centre for the Arts, 6300 Fifth Avenue, Pittsburgh.
Saturday
7:45 Continental breakfast
8:30 Five talks
Multi-tasking and Control
Duncan Brumby & Dario Salvucci, Exploring Human Multitasking Strategies from a Cognitive Constraints Approach
Dario Salvucci & Niels Taatgen, An Integrated Approach to Multitasking in ACT-R
Andrea Stocco & John Anderson, The Neural Correlates of Control States in Algebra Problem Solving
Erik Altmann & Greg Trafton, Modeling the Timecourse of Recovery from Task Interruption
Jared Danker, The Roles of Prefrontal and Posterior Parietal Cortices in Algebra Problem Solving: A Case of Using Cognitive Modeling to Inform Neuroimaging Data
10:10 Break
10:30 Five talks
Individual differences
Niels Taatgen, Ion Juvina, Seth Herd & David Jilk, A Hybrid Model of Attentional Blink
Daniel Hasumi-Dickison and Niels Taatgen, Individual differences in the Abstract Decision Making Task.
Ion Juvina, Niels A. Taatgen, & Daniel Hasumi-Dickison, The Role of Top-Down Control in Working Memory Performance: Implications for Multi-Tasking
Modeling/Architectural issues/Tools
Robert St. Amant, Sean McBride & Frank Ritter, An AI Planning Perspective on Abstraction in ACT-R Modeling
Christian Lebiere, Constraints and Complexity of Information Retrieval
12:10 Lunch
1:30 Five talks
John Anderson, Dan Bothell, Christian Lebiere & Niels Taatgen, the BICA project
Model validation
Glenn Gunzelmann & Kevin Gluck, Model Validation and High Performance Computing
Hedderik van Rijn, Complex model validation by multi-level modeling
Terrence Stewart & Robert West, ACT-R versus not-ACT-R: Demonstrating Cross-domain Validity
Simon Li & Richard Young, ACT-R ALMOST provides a formula for predicting the rate of post-completion error
3:10 Break
3:40 Future of ACT-R
Sunday
7:45 Continental breakfast
8:30 Five talks
Reasoning/problem solving
Adrian Banks, The Influence of Belief on Relational Reasoning: An ACT-R Model
Complex tasks
Michael Schoelles, Wayne D. Gray, Vladislav Veksler, Stephane Gamard, and Alex Grintsvayg, Cognitive Modeling of Web Search
Eric Raufaste, ATC in ACT-R, a model of Conflict Detection between Planes
Shawn Nicholson, Michael Byrne & Michael Fotta, Modifying ACT-R for Visual Search of Complex Displays
Shawn Nicholson, Michael Fotta, Rober St. Amant & Michael Byrne, SegMan and HEMA-SI
10:10 Break
10:30 Five talks
Emotion
Frank Ritter, Sue Kase, Michael Schoelles, Jeanette Bennett & Laura Cousino Klein, Cognitive Aspects of Serial Subtraction
Robert West, Terrence Stewart & Bruno Emond, Modeling Emotion in ACT-R
Danilo Fum, Expected values and loss frequencies: A new view on the choice process in the Iowa Gambling Task
Visual perception and Search
Troy Kelley, Visual Search
Mike Byrne, A Theory of Visual Salience Computation in ACT-R
12:10 End
Jan 18
(L to R) Rui Mata, Bruce Burns, Yvonne Kao, Adrian Banks, Jong Kim, Linnea Karlsson, Niels Taatgen, Alexandra Forsythe, Edward Cokely, Dan Bothell, Heather Dye, Jared Danker, Ion Juvina, Leendert van Maanen, Tim Halverson, Michael Fotta, John Anderson
PDF of Proceedings
Jan 18
(L to R) Niels Taatgen, Leo Ferres, Daniel Veksler, Angela Brunstein, Wolfgang Gaissmaier, John Anderson, Lissette Mol, Dan Bothell, Andrew Reifers, Raj Ratwani, Chris Sims, Renee Elio, Yelena Kushleyva
NOT PICTURED: Gisela Bahr, Scott Kerick
ELEVENTH ANNUAL ACT-R SUMMER SCHOOL
===================================
Carnegie Mellon University – July 2004
======================================
ACT-R is a cognitive theory and simulation system for developing cognitive
models for tasks that vary from simple reaction time to air traffic control.
The most recent advances of the ACT-R theory were detailed in the recent
book “The Atomic Components of Thought” by John R. Anderson and Christian
Lebiere, published in 1998 by Lawrence Erlbaum Associates, and in a paper
available online (http://act-r.psy.cmu.edu/papers/403/IntegratedTheory.pdf).
Each year, a summer school is held to train researchers in the use
of the ACT-R system. This year the summer school is followed by the International
Conference on Cognitive Modeling, which will also be in Pittsburghfrom July 30
until August 1. See http://simon.lrdc.pitt.edu/~iccm/ for details.
The Eleventh Annual ACT-R Summer School will be held at Carnegie Mellon University
in Pittsburgh in July 2004.
The summer school will take place from Friday July 23 to Wednesday July 28.
This intensive 6-day course is designed to train researchers in the use of
ACT-R for cognitive modeling. It is structured as a set of six units, with
each unit lasting a day and involving a morning theory lecture, a web-based tutorial,
an afternoon discussion session and a homework assignment which participants
are expected to complete during the day and evening. Computing facilities will be provided.
To provide an optimal learning environment, admission is limited to a dozen participants,
who must submit by April 20 an application consisting of a curriculum vitae and a
statement of purpose. Demonstrated experience with a modeling formalism similar to
ACT-R will strengthen the application. Applicants will be notified of admission by May 4,
with early notification upon request. Admission to the summer school is free.
More information, including papers published by the ACT-R community, can be found
on the ACT-R web site (http://act-r.psy.cmu.edu/).
A registration form is appended below. Additional information (detailed
schedule, etc.) will appear on the ACT-R Web site when available or can be
requested at:
2004 ACT-R Summer School
Psychology Department
Attn: Niels Taatgen
Baker Hall 345E Fax: +1 (412) 268-2844
Carnegie Mellon University Tel: +1 (412) 268-2815
Pittsburgh, PA 15213-3890 Email: taatgen@cmu.edu
________________________________________________________
Eleventh Annual ACT-R Summer School and Workshop
July 23 to 28, 2004 at Carnegie Mellon University in Pittsburgh
REGISTRATION
============
Name: …………………………………………………………
Address: …………………………………………………………
…………………………………………………………
…………………………………………………………
Tel/Fax: …………………………………………………………
Email:
…………………………………………………………
Summer School (July 23 to 28)
=============================
Applications are due APRIL 20. Acceptance will be notified by MAY 4.
Applicants MUST include a curriculum vitae and a short statement of purpose.
Demonstration of experience with a modeling formalism similar to ACT-R,
such as a completed model, should also be included in the application.
HOUSING
=======
Housing is available in Resnick House, a CMU dormitory that offers
suite-style accommodations. Rooms include air-conditioning, a semi-private
bathroom and a common living room for suite-mates. Last year’s rates were
$267.75/week/person or $38.25/night/person for single rooms and
$192.50/week/person or $27.50/night/person for double rooms. Housing
reservations will be taken after acceptance to the summer school. Do not
send money. See http://www.housing.cmu.edu for further housing information.
To reserve a room in Resnick House, fill in the dates and select one of the
three room options:
I will stay from ……………. to …………….
1. … I want a single room
2. … I want a double room and I will room with …………….
3. … I want a double room. Please select a roommate of ……. gender
ROOM PAYMENT IS DUE UPON CHECK-IN. DO NOT SEND MONEY.
The recommended hotel is the Wyndham Garden Hotel, located within easy
walking distance of CMU. Contact the Wyndham directly at +1 (877) 662 6242.
Send this form to:
2004 ACT-R Summer School
Psychology Department
Niels Taatgen
Baker Hall 345E Fax: +1 (412) 268-2844
Carnegie Mellon University Tel: +1 (412) 268-2815
Pittsburgh, PA15213-3890 Email: taatgen@cmu.edu
Jan 18
Front Row: (L to R) Dan Bothell, Sue Kase, Simon Li, Sarah Peterson-Everett, Deborah Boehm-Davis, Phil Pavlik
Back Row: (L to R) Glenn Gunzelmann, Dario Salvucci, Shavan Vasishth, Scott Douglass, Carl Smith, Norbu Buchler, Christopher Myers, Christian Lebiere, Dan Schunk, John Anderson, Raluca Budiu, Annes Fowles-Winkler, Niels Taatgen, Hedderik van Rijn, Sally Bogacz, Fransisco Pereira, Martin Greaves
2003 ACT-R Workshop Schedule
Friday, July 25
Talk Session 1
Talk Session 2
Future of ACT-R
Invited Session
Saturday, July 26
Talk Session 3
Talk Session 4
Sunday, July 27
Talk Session 5
Talk Session 6
Jan 18
(L to R) Hedderk van Rijn, Raluc Buidu, Magdalena Bugaska, Niels Taatgen, Gwendolyn Campbell, Christian Lebiere, John Anderson, Daniel Carruth, Dan Bothell, Hansjoerg Neth, Susan Chipman, Tim Nokes, Laurel Allender, Marios Avraamides, Jerry Ball, Stephanie Lackey
2002 ACT-R Workshop Schedule
Friday August 2
8:30 AM Talk Session 1
John Anderson, Yulin Qin, Myeong-Ho Sohn, Andy Stenger and
Cam Carter
Symbol Fun: ACT-R�s brain changes with practice
Stefani Nellen
The take the best heuristic and ACT-R
Timothy J. Nokes, Stellan Ohlsson and Andrew Corrigan-Halpern
Learning by analogy vs learning by instruction: Same knowledge, different representations
Greg Trafton
Playing hide and seek without perspective-taking:�A learning model
10:30 AM Talk Session 2
John Anderson, Dan Bothell, Scott Douglass, Craig Haimson and Myeong-Ho Sohn
CMU-ASP: ACT-R learns to be an anti-air warfare coordinator
Jerry Ball, Kevin Gluck, Michael Krusmark, Mathew Purtee and Stu Rodgers
Process and challenges in development of the Predator air vehicle operator model
Bradley Best, Christian Lebiere and Chris Scarpinatto
Modeling synthetic opponents in urban combat simulations
Niels Taatgen, Marcia van Oploo, Jos Braaksma and Jelle Niemantsverdriet
From model to application: developing a believable opponent in the game of Set!
12:10 PM Lunch
1:00 PM The Future of ACT-R
Christian Lebiere ACT-R 5.0 and 6.0
Niels Taatgen Production compilation
Frank Ritter The ACT-R FAQ
Eli Silk The New ACT-R web page
Mike Byrne The current state of ACT-R/PM
Anthony Harrison jACT-R: Beta and Beyond
Dan Bothell The new ACT-R environment
3:00 PM Invited Session
Richard Cooper Mechanisms of sequential control
John Anderson Response
Saturday
8:30 AM Talk Session 3
Mike Byrne
ACT-R as a framework for modeling human error
Troy Kelley
Modeling situation awareness errors in a navigation task
Dirk van Rooy, Frank E. Ritter and Robert St. Amant
Using a simulated user to explore human-robot interfaces
Robert West and Bruno Emond
SOS: A Simple Operating System for modeling HCI with ACT-R
10:30 AM Talk Session 4
Mike Byrne, David Maurier and Christopher Fick
Reaping the rewards of teaching ACT-R: Class projects Spring 2002
Cleotilde Gonzalez
Modeling coordination in team dynamic resource allocation
Glenn Gunzelmann and John R. Anderson
Performance differences between strategies in an orientation task
David Huss
An ACT-R/PM model of the articulatory loop
1:00 PM Talk Session 5
Mon-Chu Chen
Cognitive approaches to gaze tracking
Todd R. Johnson, Hongbing Wang, Jiajie Zhang and Yue Wang
Memory for multidimension stimuli
David Peebles
Investigating the incidental learning of location information in a visual search task
Hongbin Wang
Modeling human attention networks
3:00 PM Comparative Architectures Symposium
B. Chandrasekaran Multimodal representation as basis for cognitive architecture
Michael Freed Behavior representation in Apex
Sunday
8:30 AM Talk Session 6
Erik Altmann
Switch cost: A failed measure of executive control
Raluca Budiu
Can ACT-R process language in real-time?� Putting together syntactic and semantic processing
Hedderik Van Rijn
Modeling developmental transitions. A proceduralization model of balance scale learning
Richard Young
Random walk processes in ACT-R mechanisms lead to a wild distribution of learning times
10:30 AM Talk Session 7
Kwangsu Cho and Christian Schunn
Strategy shift in prisoner�s dilemma through utility learning
Danilo Fum and Andrea Stocco
Procedural learning in the control of a dynamic system
Christian Lebiere
AMBR III: A simple, predictive, architectural model of categorization in the wild
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