Marc Pickett

RepLearn 2013

I'm the main contact on the organizing committee for the AAAI 2013 Workshop on Learning Rich Representations from Low-Level Sensors.

Publications

I am also on Google Scholar and DBLP.
Overview slides of my research ca. 2013/03/20.

 
• Pickett, M. and Aha, D.W.
  Using Cortically-Inspired Algorithms for Analogical Learning and Reasoning
  (Preprint accepted for publication) In Biologically Inspired Cognitive Architectures, 2013.
   
• Pickett, M.
  Building on Deep Learning
  (Preprint accepted for publication) In AAAI Workshop on Learning Rich Representations from Low-Level Sensors, 2013.
   
• Pickett, M. and Aha, D.W.
  Spontaneous Analogy by Piggybacking on a Perceptual System
  (Preprint accepted for publication) In Proceedings of the 35th Annual Meeting of the Cognitive Science Society (CogSci-2013) , 2013.
   
• Heitmeyer, C., Pickett, M., Breslow, L., Aha, D.W., Trafton, J.G., and Leonard, E.I.
  High Assurance Human-Centric Decision Systems
  (Preprint accepted for publication) In Proceedings of the 2nd International NSF sponsored Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE'13), 2013.
   
• Pickett, M., Aha, D.W., and Trafton, J.G.
  Acquiring User Models to test Automated Assistants
  (Preprint accepted for publication) In Proceedings of the Twenty-Sixth International Florida Artificial Intelligence Research Society Conference (FLAIRS-26) , 2013.
   
• Pickett, M.
  Towards Relational Theory Formation from Undifferentiated Sensor Data.
  Doctoral Dissertation, University of Maryland, Baltimore County, 2011. [defense slides]
   
• Pickett, M., Miner, D., and Oates, T.
  Essential Phenomena of General Intelligence.
  In Proceedings of The First Conference on Artificial General Intelligence, 2008.
   
• Pickett, M., Miner, D.
  Representation Change in The Marchitecture.
  In Working Notes of the AAAI Fall Symposium on Representation Change, 2007.
   
• Pickett, M., Miner, D., and Oates, T.
  A Gauntlet for Evaluating Cognitive Architectures.
  In Working Notes of the AAAI Workshop on Evaluating Architectures for Intelligence, 2007.
   
• Pickett, M. and Oates, T.
  The Marchitecture: A Cognitive Architecture for a Robot Baby.
  In Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-07), (student abstract and poster), 2007.
   
• Pickett, M.
  The Übercruncher: Concept Formation by Analogy Discovery.
  In Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI-07), Doctoral Consortium, 2007.
   
• Pickett, M.
  Using Analogy Discovery to Create Abstractions.
  In proceedings of the 7th International Symposium on Abstraction, Reformulation and Approximation (SARA 2007), Lecture Notes in Artificial Intelligence. Springer Verlag, 2007.
   
• Chaddock, G., Pickett, M., Armstrong, T., and Oates, T.
  Models of Strategic Deficiency and Poker.
  In Working Notes of the AAAI Workshop on Plan, Activity, and Intent Recognition (PAIR), 2007.
   
• Pickett, M. and Oates, T.
  The Cruncher: Automatic Concept Formation using Minimum Description Length.
  In proceedings of the 6th International Symposium on Abstraction, Reformulation and Approximation (SARA 2005), Lecture Notes in Artificial Intelligence. Springer Verlag, 2005.
   
• Berry, N., Ko, T., Moy, T., Pickett, M., Smrcka, J., Turnley, J., and Wu, B.
  Computational Social Dynamic Modeling of Group Recruitment.
  Sandia Report SAND2003-8754, Sandia National Laboratories, 2003.
   
• Pickett, M.
  Research Summary.
  In proceedings of the 5th International Symposium on Abstraction, Reformulation and Approximation (SARA 2002), Lecture Notes in Artificial Intelligence. Springer Verlag, 2002.
   
• Pickett, M. and Barto, A.G.
  Policyblocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning.
  In Proceedings of the International Conference on Machine Learning, 2002.