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Scaling Properties of Coarse-Coded Symbol Memories.

, and . NIPS, page 652-661. American Institue of Physics, (1987)

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Rules and Maps II: Recent Progress in Connectionist Symbol Processing, , and . CMU-CS-90-112. Computer Science Department, Carnegie Mellon University, Pittsburgh, PA, (1990)Calypso for Cozmo: Robotic AI for Everyone (Abstract Only)., and . SIGCSE, page 1110. ACM, (2018)A Computational Basis for Phonology, and . Advances in Neural Information Processing Systems 2, San Francisco, CA: Morgan Kaufmann, (1990)Symbols Among the Neurons: Details of a Connectionist Inference Architecture., and . IJCAI, page 238-243. Morgan Kaufmann, (1985)AI for K-12: Making Room for AI in K-12 CS Curricula., , , and . SIGCSE, page 1244. ACM, (2019)Evaluating the Effect of Using Physical Manipulatives to Foster Computational Thinking in Elementary School., , and . SIGCSE, page 9-14. ACM, (2017)Envisioning AI for K-12: What Should Every Child Know about AI?, , , and . AAAI, page 9795-9799. AAAI Press, (2019)BOF: Organizing State-Level Efforts for K-12 AI Education., , , , and . SIGCSE (2), page 1242. ACM, (2023)Timing and Partial Observability in the Dopamine System., , and . NIPS, page 83-90. MIT Press, (2002)Scaling Properties of Coarse-Coded Symbol Memories., and . NIPS, page 652-661. American Institue of Physics, (1987)