ACT-R » Tools

Zhang, Q., Borst, J.P., ,Kass, R. E., & Anderson, J.R. (2017) Inter-subject Alignment of MEG Datasets in a Common Representational Space. Human Brain Mapping. 38. 4287–4301.

Anderson, J.R., Zhang, Q., Borst, J.P., & Walsh, M.M. (2016). The Discovery of Processing Stages: Extension of Sternberg’s Method. Psychological Review, 123(5), 481-509.

Dörr, L.-M., Russwinkel, N. and Prezenski, S. (2016). ACT-Droid: ACT-R interacting with Android applications. In D. Reitter & F. E. Ritter (Eds.), Proceedings of the 14th International Conference on Cognitive Modeling. University Park, PA: Penn State.

Lebiere, C., Bennati, S., Thomson, R., Shakarian, P., & Nunes, E. (2015). Functional Cognitive Models of Malware Identification. In N. Taatgen (Ed), Proceedings of the 13th Annual Conference on Cognitive Modeling. Groningen, Netherlands.

Thomson, R. Lebiere, C., Bennati, S., Shakarian, P., & Nunes, E. (2015). Malware Identification Using Cognitively-Inspired Inference. In Proceedings of the 24th Annual Behavior Representation in Modeling and Simulation Conference. Washington, DC.

Thomson, R. Lebiere, C., & Bennati, S. (2014). Human, Model, and Machine: A Complementary Approach to Big Data. In Association for Computing Machinery Proceedings of the IARPA Workshop on Human Centered Big Data Research. Raleigh, NC. doi:10.1145/2609876.2609883

Process models of cognition, written in architectures such as ACT-R and EPIC, should be able to interact with the same software with which human subjects interact. By eliminating the need to simulate the experiment, this approach would simplify the modeler’s effort, while ensuring that all steps required of the human are also required by the model. In practice, the difficulties of allowing one software system to interact with another present a significant barrier to any modeler who is not also skilled at this type of programming. The barrier increases if the programming language used by the modeling software differs from that used by the experimental software. The JSON Network Interface simplifies this problem for ACT-R modelers, and potentially, modelers using other systems.

Halbrügge, M. (2013). ACT-CV: Bridging the Gap between Cognitive Models and the Outer World. In Brandenburg, E., Doria, L., Gross, A., Güntzler, T., and Smieszek, H., eds., Grundlagen und Anwendungen der Mensch-Technik- Interaktion. 10. Berliner Werkstatt Mensch-Maschine-Systeme, pages 205-210, Berlin, Universitätsverlag der TU Berlin

Büttner, P. (2010). "Hello Java": Linking ACT-R 6 with a Java Simulation. In D. D. Salvucci & G. Gunzelmann (Eds.), Proceedings of the 10th International Conference on Cognitive Modeling (pp. 289-290). Philadelphia, PA: Drexel University.

Best, B., Fincham, J., Gluck, K., Gunzelmann, G., & Krusmark, M. (2008). Efficient Use of Large-Scale Computational Resources. In J. Hansberger (Ed.), Proceedings of the Seventeenth Conference on Behavior Representation in Modeling and Simulation (pp. 180-181). Orlando, FL: Simulation Interoperability Standards Organization.

Gunzelmann, G., Pope, A., Wray, R., Best, B. J. & Trafton, J. G. (2008). Integrating cognitive architectures with external environments: Approaches and contributions to validation. In B. C. Love, K. McRae, & V. M. Sloutsky (Eds.), Proceedings of the Thirteenth Annual Meeting of the Cognitive Science Society (pp. 913-914). Austin, TX: Cognitive Science Society.

St. Amant, R., McBride, S. P., Ritter, F. E. (2007). AI support for building cognitive models. In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-06) (pp. 1663-1666). Menlo Park, CA: AAAI Press.

Heiberg, A., Harris, J., & Ball, J. T. (2007). Dynamic visualization of ACT-R declarative memory structure. In proceedings of the 8th International Conference on Cognitive Modeling. Ann Arbor, Michigan, USA.

Matessa, M. P., Archer, R., & Mui, R. (2007). Dynamic spatial reasoning capability in a graphical interface evaluation tool. In proceedings of the 8th International Conference on Cognitive Modeling. Ann Arbor, Michigan, USA.

Gluck, K .A., Scheutz, M., Gunzelmann, G., Harris, J., & Kershner, J. (2007). Combinatorics meets processing power: Large-scale computational resources for BRIMS. In T. Kelley & Allender, Proceedings of the 2007 Behavior Representation in Modeling and Simulation (BRIMS) Conference (pp. 73-83). Orlando, FL: Simulation Interoperability Standards Organization.

Heinath, M., Dzaack, J., Wiesner, A. & Urbas, L. (2007). Simplifying the Development and the Analysis of Cognitive Models. In proceedings of EuroCogSci07. Delphi, Greece.

Heinath, M. & Urbas, L. (2007). Simplifying the Development of Cognitive Models using Pattern-based Modeling. In proceedings of the 10th IFAC/IFIP/IFORS/IEA Symposium on Analysis, Design, and Evaluation of Human-Machine Systems. Seoul, Korea.

Bothell, D. (2007). ACT-R 6.0 Reference Manual. From the ACT-R Web site: http://act-r.psy.cmu.edu/wordpress/wp-content/themes/ACT-R/actr6/reference-manual.pdf.

Jones, R. M., Crossman, J. A., Lebiere, C., & Best, B. J. (2006). An abstract language for cognitive modeling. In Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 160-165). Trieste, Italy.

Ritter, F. E., Haynes, S. R., Cohen, M., Howes, A., John, B., Best, B. J., Lebiere, C., Jones, R. M., Crossman, J., Lewis, R. L., St. Amant, R., McBride, S. P., Urbas, L., Leuchter, S., & Vera, A. (2006). High-level behavior representation languages revisited. Symposium at Trieste: Proceedings of the Seventh International Conference on Cognitive Modeling (pp. 404-407). Trieste, Italy.

St. Amant, R., Riedl, M. O., Ritter, F. E., & Reifers, A. (2005). Image processing in cognitive models with SegMan. In Proceedings of HCI International, 2005. (Invited.) Volume 4 - Theories Models and Processes in HCI. Paper # 1869.

John, B. E. & Salvucci, D. D. (2005) Multi-Purpose Prototypes for Assessing User Interfaces in Pervasive Computing Systems. IEEE Pervasive Computing 4(4), 27-34.

St. Amant, R., Freed, A. R., & Ritter, F. E. (2005). Specifying ACT-R models of user interaction with a GOMS language. Cognitive Systems Research, 6, 71-88.

St. Amant, R. & Ritter, F. E. (2004). Automated GOMS-to-ACT-R model generation. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 26-31). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

Tor, K., Haynes, S. R., Ritter, F. E., & Cohen, M. A. (2004). Categorical data displays generated from three cognitive architectures illustrate their behavior. In Proceedings of the International Conference on Cognitive Modeling (pp. 302-307). Mahwah, NJ: Lawrence Erlbaum.

Tor, K. & Ritter, F. E. (2004). Using a genetic algorithm to optimize the fit of cognitive models. In Proceedings of the Sixth International Conference on Cognitive Modeling. Mahwah, NJ: Lawrence Erlbaum.

John, B. E., Prevas, K., Salvucci, D. D., Koedinger, K. (2004) Predictive human performance modeling made easy. In Proceedings of CHI 2004 (Vienna, Austria, April 2004), ACM New York. 455-462.

John, B. E., Salvucci, D. D., Centgraf, P., Prevas, K. (2004). Integrating models and tools in the context of driving and in-vehicle devices. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 130-135). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

West, R. L. & Emond, B. (2004). The environment as theory: An example using the ACT-R/SOS environment. In Proceedings of the sixth International Conference on Cognitive Modeling (pp. 398-399). Pittsburgh, PA: Carnegie Mellon University/University of Pittsburgh.

Tor, K., Ritter, F. E., Haynes, S. R., & Cohen, M. A. (2004). CaDaDis: A tool for displaying the behavior of cognitive models and agents. In Proceedings of the 13th Conference on Behavior Representaion in Modeling and Simulation. 04-BRIMS-032. 192-200. Orlando, FL: University of Central Florida.

Howes, A., Vera, A., Lewis, R. L., & McCurdy, M. (2004). Cognitive constraint modeling: A formal approach to supproting reasoning about behavior. In proceedings of the 26th Annual Conference of the Cognitive Science Society (pp.595-600) . August 4-7, Chicago, USA

Matessa, M. (2004) An ACT-R modeling framework for interleving templates of human behavior. In proceedings of the 26th Annual Conference of the Cognitive Science Society (pp. 903-908) . August 4-7, Chicago, USA

St. Amant, R., Horton, T. E., & Ritter F. E. (2004). Model-based evaluation of cell phone menu interaction. In Proceedings of the CHI'04 Conference on Human Factors in Computer Systems 343-350. New York, NY: ACM.

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