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MindModeling@Home

From Wikipedia, the free encyclopedia
BOINC based volunteer computing project researching cognitive science
MindModeling@Home
interactive screensaver
Initial releaseMarch 17, 2007 (2007-03-17)
Development statusInactive
Operating systemCross-platform
PlatformBOINC
Average performance0GFLOPS,[1]
Active users0
Total users0
Active hosts0
Total hosts0
Websitemindmodeling.org

MindModeling@Home[2] is an inactive non-profit,volunteer computing research project for the advancement ofcognitive science. MindModeling@Home is hosted byWright State University and theUniversity of Dayton in Dayton, Ohio.

InBOINC, it is in the area of Cognitive Science and category called Cognitive science and artificial intelligence.[3] It can only operate on a 64-bit operating system, preferably on a computer with multiple cores, running aMicrosoft Windows,Mac OS X, orLinux operating system. This project is not compatible with mobile devices, unlike other projects on BOINC.

Research focus

[edit]
  • N-2 Repetition: understanding how people have a harder time returning to a task from another one
  • Observing how people read through their eye movement for the purpose of helping people reduce eye strain and processing what they read better and faster.
  • Modeling decision-making: resolving around decisions made from visual processing (focus and filtering)
  • Integrated Learning Models (ILM) to create algorithms based on how people learn and make decisions
  • How the brain performs tasks sequentially and simultaneously by measuring its blood flow[4]

Problems

[edit]
  • Its status is inactive.[5] However, it is "not down or closed,"[6] as its servers are still running.[7]
  • The projects are long; prolonged amounts of computing time can overheat a computer. The solution is to stop work on the project until the computer cools down.[8]
  • It is subject to power outages, as seen on October 7, 2018[9]
  • When the website will be out ofbeta mode is unknown, as it has been in beta since 2007[10]

Scientific results

[edit]
  1. Godwin H.J., Walenchok S. et al. Faster than the speed of rejection: Object identification processes during visual search for multiple targets. J Exp Psychol Hum Percept Perform. 41–4, (2016).[11]
  2. Moore L. R., Gunzelmann G. An interpolation approach for fitting computationally intensive models. Cognitive Systems Research 19, (2014).[12]
  3. Moore L.R. Cognitive model exploration and optimization: a new challenge for computational science. Comput Math Organ Theory 17, 296–313. (2011).[13]
  4. Moore L.R., Kopala M., Mielke T. et al. Simultaneous performance exploration and optimized search with volunteer computing. 19th ACM International Symposium on High Performance Distributed Computing, (2010).[14]
  5. Harris J., Gluck K.A., Moore L.R. MindModeling@Home. . . and Anywhere Else You Have Idle Processors. 9th International Conference on Cognitive Modelling, (2009).[15]
  6. Gluck K., Scheutz M.Combinatorics meets processing power: Large-scale computational resources for BRIMS. 16th Conference on Behavior Representation in Modeling and Simulation, BRIMS. 1. 73–83. (2007).[16]

See also

[edit]

References

[edit]
  1. ^de Zutter W."MindModeling@Home: Credit overview". boincstats.com.Archived from the original on 2022-03-01. Retrieved2023-06-18.
  2. ^Moore, L. Richard; Kopala, Matthew; Mielke, Thomas; Krusmark, Michael; Gluck, Kevin A. (2010-06-21)."Simultaneous performance exploration and optimized search with volunteer computing".Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing. HPDC '10. New York, NY, USA: Association for Computing Machinery. pp. 312–315.doi:10.1145/1851476.1851518.ISBN 978-1-60558-942-8.S2CID 18679055.Archived from the original on 2022-09-05. Retrieved2022-08-14.
  3. ^"Choosing BOINC projects".boinc.berkeley.edu.Archived from the original on 2018-01-03. Retrieved2019-07-13.
  4. ^"Projects Overview".mindmodeling.org.Archived from the original on 2019-07-12. Retrieved2019-07-13.
  5. ^"MindModeling@Home - BOINC".boinc.berkeley.edu.Archived from the original on 2019-03-06. Retrieved2019-07-13.
  6. ^"Hails and Farewells".mindmodeling.org.Archived from the original on 2018-08-17. Retrieved2019-07-13.
  7. ^"Project status".mindmodeling.org.Archived from the original on 2019-07-13. Retrieved2019-07-13.
  8. ^"Read our rules and policies".mindmodeling.org.Archived from the original on 2019-07-13. Retrieved2019-07-13.
  9. ^"MindModeling@Home (Beta)".mindmodeling.org.Archived from the original on 2019-07-13. Retrieved2019-07-13.
  10. ^"When will mindmodeling@home be out of beta".mindmodeling.org.Archived from the original on 2018-08-27. Retrieved2019-07-13.
  11. ^Godwin, Hayward J.; Walenchok, Stephen C.; Houpt, Joseph W.; Hout, Michael C.; Goldinger, Stephen D. (August 2015)."Faster than the speed of rejection: Object identification processes during visual search for multiple targets".Journal of Experimental Psychology: Human Perception and Performance.41 (4):1007–1020.doi:10.1037/xhp0000036.ISSN 1939-1277.PMC 4516661.PMID 25938253.
  12. ^Richard Moore, L.; Gunzelmann, Glenn (2014-09-01)."An interpolation approach for fitting computationally intensive models".Cognitive Systems Research.29–30:53–65.doi:10.1016/j.cogsys.2013.09.001.ISSN 1389-0417.S2CID 26656979.
  13. ^Moore, L. Richard (2011-09-01)."Cognitive model exploration and optimization: a new challenge for computational science".Computational and Mathematical Organization Theory.17 (3):296–313.doi:10.1007/s10588-011-9092-8.ISSN 1572-9346.S2CID 7767242.
  14. ^Moore, L. Richard; Kopala, Matthew; Mielke, Thomas; Krusmark, Michael; Gluck, Kevin A. (2010-06-21)."Simultaneous performance exploration and optimized search with volunteer computing".Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing. HPDC '10. New York, NY, USA: Association for Computing Machinery. pp. 312–315.doi:10.1145/1851476.1851518.ISBN 978-1-60558-942-8.S2CID 18679055.
  15. ^"Mindmodeling@Home. . . and Anywhere Else You Have Idle Processors".{{cite journal}}:Cite journal requires|journal= (help)
  16. ^"ACT-R » Publications » Combinatorics meets processing power: larger-scale computational resources for BRIMS". Retrieved2022-10-09.

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