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Machine Learning Approaches to Cognitive Parameter Acquisition Terran Lane University of New Mexico [email_address] Chris Forsythe, Patrick Xavier Sandia National Labs {jcforsy,pgxavie}@sandia.gov
Sandia’s Cognitive Modeling Framework ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Big Picture World Cue 0   0 Cue 1   1 Cue N   N Situation 0 Situation 1 Situation M Actions/ Decisions  01  10  N1  NM 
Automated Model Acquisition ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Roles for Machine Learning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Parameter Acquisition World Cue 0   0 Cue 1   1 Cue N   N Situation 0 Situation 1 Situation M Actions/ Decisions  01  10  N1  NM 
Parameter Acquisition: Issues ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Parameter Acquisition:  Approaches ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Network Topology Induction World Cue 0   0 Cue 1   1 Cue N   N Situation 0 Situation 1 Situation M Actions/ Decisions  01  10  N1  NM 
Topology Induction: Issues ,[object Object],[object Object],[object Object]
Topology Induction: Issues ,[object Object],[object Object],[object Object],L=137
Topology Induction: Issues ,[object Object],[object Object],[object Object],L=137 L=238
Topology Induction: Issues ,[object Object],[object Object],[object Object],L=137 L=238 L=493
Topology Induction: Issues ,[object Object],[object Object],[object Object],L=137 L=238 L=493 L=318
Topology Induction: Issues ,[object Object],[object Object],[object Object],L=137 L=238 L=493 L=318
Topology Induction: Approaches ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Cue and Situation Identification World Cue 0   0 Cue 1   1 Cue N   N Situation 0 Situation 1 Situation M Actions/ Decisions  01  10  N1  NM 
Cue and Situation Identification: Issues ,[object Object],[object Object],[object Object],N=2 N=3
Cue and Situations: Approaches ,[object Object],[object Object],[object Object],[object Object]
Conclusions ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Questions?

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Machine Learning Methods for Parameter Acquisition in a Human ...

  • 1. Machine Learning Approaches to Cognitive Parameter Acquisition Terran Lane University of New Mexico [email_address] Chris Forsythe, Patrick Xavier Sandia National Labs {jcforsy,pgxavie}@sandia.gov
  • 2.
  • 3. The Big Picture World Cue 0  0 Cue 1  1 Cue N  N Situation 0 Situation 1 Situation M Actions/ Decisions  01  10  N1  NM 
  • 4.
  • 5.
  • 6. Parameter Acquisition World Cue 0  0 Cue 1  1 Cue N  N Situation 0 Situation 1 Situation M Actions/ Decisions  01  10  N1  NM 
  • 7.
  • 8.
  • 9. Network Topology Induction World Cue 0  0 Cue 1  1 Cue N  N Situation 0 Situation 1 Situation M Actions/ Decisions  01  10  N1  NM 
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17. Cue and Situation Identification World Cue 0  0 Cue 1  1 Cue N  N Situation 0 Situation 1 Situation M Actions/ Decisions  01  10  N1  NM 
  • 18.
  • 19.
  • 20.