Project Tabula Rasa is an umbrella term for a few software, system, and (eventual) hardware projects modeled after the generalized intelligence exhibited by the human mind. These intensely detailed and interconnected projects are the product of academic research started in 2005 collaborating knowledge from the interdisciplinary study of Computer Science, Mathematics, Physics, Neurobiology, Psychology, Philosophy, Literature, Cognitive Science, and Education.

    Some sub-projects include:
  • Dynamic Load Balancing for Dynamic Distributed Networks
  • Invariant Representations of Temporal Percept Sequences
  • Scalable Distributed Cortical System Design
  • Modular, On-line, Competitive, Unsupervised Machine Learning Algorithms
    This is a massive theoretical undertaking which will result in several publications. The academic papers that have contributed to my knowledge have not been cataloged (yet), but a list of books that I use as reference/inspiration materials include (but is not limited to):
  1. Understanding Human Behavior (Vols. 1-24)
  2. MIT Encyclopedia of the Cognitive Sciences
  3. Cambridge Handbook of Thinking & Reasoning
  4. Handbook of Brain Theory and Neural Networks – Arbib
  5. Connectionism and the Mind – Bechtel/Abrahamsen
  6. Minds and Computers – Carter
  7. Decision Fusion – Dasarathy
  8. Pattern Classification – Duda/Hart/Stork
  9. Artificial Dreams – Ekbia
  10. From Molecule to Metaphor – Feldman
  11. Markov Models for Pattern Recognition – Fink
  12. Emotion Science – Fox
  13. Gut Feelings – Gigerenzer
  14. The Hidden Pattern – Goertzel
  15. Artificial General Intelligence – Goertzel
  16. Robot Brains – Haikonen
  17. Beyond AI – Hall
  18. On Intelligence – Hawkins
  19. The Art of Multiprocessor Programming – Herlihy/Shavit
  20. The Chemistry of Conscious States – Hobson
  21. Gödel, Escher, Bach – Hofstadter
  22. Human Memory – Howes
  23. Modern Multivariate Statistical Techniques – Izenman
  24. Dynamical Systems in Neuroscience – Izhikevich
  25. Innovations in ART Neural Networks – Jain
  26. In Search of Memory – Kandel
  27. Programming Massively Parallel Processors – Kirk/Whu
  28. The Emotional Brain – Ledoux
  29. How We Decide – Lehrer
  30. Proust Was a Neuroscientist – Lehrer
  31. Complexity – Lewin
  32. Big Brain – Lynch/Granger
  33. Cognition – Matlin
  34. Learning & Instruction – Mayer
  35. Mind and Mechanism – McDermott
  36. Cracking Creativity – Michalko
  37. The Emotion Machine – Minsky
  38. The Society of Mind – Minsky
  39. Machine Learning – Mitchell
  40. How People Learn – National Research Council
  41. The Human Brain – Nolte
  42. The Emperor's New Mind – Penrose
  43. Motivation – Petri/Govern
  44. An Introduction to Information Theory – Pierce
  45. Artificial Beings – Pitrat
  46. Remembrance of Things Past – Proust
  47. Semantic Cognition – Rogers/McClelland
  48. Parallel Distributed Processing Vol 1 & 2 – Rumelhart/McClelland/the PDP Research Group
  49. Artificial Intelligence – Russel/Norvig
  50. CUDA by Example – Sanders/Kandrot
  51. The Quantum Brain – Satinover
  52. Nonlinear Regression – Seber/Wild
  53. Programming Collective Intelligence – Segaran
  54. Kernel Methods – Shawe-Taylor/Cristianini
  55. Fundamentals of Physiology – Sherwood
  56. Contemporary Debates in Cognitive Science – Stainton
  57. Nonlinear Dynamics and Chaos – Strogatz
  58. Distributed Systems Principles and Paradigms – Tanenbaum/Van Steen
  59. Pattern Recognition – Theodoridis/Koutrounbas
  60. The Computer and The Brain – von Neumann
  61. Parallel Programming – Wilkinson/Allen
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