What is the Ground ? Continuous Maps for Grounding Perceptual Primitives

Analysis of the Symbol Grounding Problem has typically focused on the nature of symbols and how they tie to perception without focusing on the actual qualities of what the symbols are to be grounded in. We formalize the requirements of the ground and propose a basic model of grounding perceptual primitives to regions in perceptual space that demonstrates the significance of continuous mapping and how it influences categorization and conceptualization of perception. We also outline methods to incorporate continuous grounding into computational systems and the benefits of applying such constraints.

[1]  David C. Plaut,et al.  Semantic and Associative Priming in a Distributed Attractor Network , 1995 .

[2]  D. Buonomano,et al.  Cortical plasticity: from synapses to maps. , 1998, Annual review of neuroscience.

[3]  A. Parker,et al.  Sense and the single neuron: probing the physiology of perception. , 1998, Annual review of neuroscience.

[4]  Stevan Harnad.  The Symbol Grounding Problem , 1999, ArXiv.

[5]  L. Barsalou,et al.  Whither structured representation? , 1999, Behavioral and Brain Sciences.

[6]  Alexander Borst,et al.  Information theory and neural coding , 1999, Nature Neuroscience.

[7]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[8]  J. Davidoff,et al.  Color categories are not universal: replications and new evidence from a stone-age culture. , 2000, Journal of experimental psychology. General.

[9]  Dmitri B. Chklovskii,et al.  Orientation Preference Patterns in Mammalian Visual Cortex A Wire Length Minimization Approach , 2001, Neuron.

[10]  P. Gärdenfors.  Conceptual spaces as a framework for knowledge representation , 2004 .

[11]  Brian A Wandell,et al.  Visual field map clusters in human cortex , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[12]  Thomas Mormann,et al.  Natural predicates and topological structures of conceptual spaces , 1993, Synthese.

[13]  Michael M Merzenich,et al.  Perceptual Learning Directs Auditory Cortical Map Reorganization through Top-Down Influences , 2006, The Journal of Neuroscience.

[14]  John G. Flanagan,et al.  Development of Continuous and Discrete Neural Maps , 2007, Neuron.

[15]  J. MacDonald,et al.  Hearing Lips and Seeing Voices: Illusion and Serendipity in Auditory‐Visual Perception Research , 2008 .

[16]  Ali Farhadi,et al.  Describing objects by their attributes , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[17]  N. Sobel,et al.  An odor is not worth a thousand words: from multidimensional odors to unidimensional odor objects. , 2013, Annual review of psychology.

[18]  Fei-Fei Li,et al.  Attribute Learning in Large-Scale Datasets , 2010, ECCV Workshops.

[19]  Jack L. Gallant,et al.  A Continuous Semantic Space Describes the Representation of Thousands of Object and Action Categories across the Human Brain , 2012, Neuron.

[20]  D. Baranes,et al.  Dendritic Branch Intersections Are Structurally Regulated Targets for Efficient Axonal Wiring and Synaptic Clustering , 2013, PloS one.

[21]  James F. Allen,et al.  SALL-E: Situated Agent for Language Learning , 2013, AAAI.

[22]  Arvind Ramanathan,et al.  Categorical Dimensions of Human Odor Descriptor Space Revealed by Non-Negative Matrix Factorization , 2013, PloS one.

[23]  Lauren L. Emberson,et al.  Is statistical learning constrained by lower level perceptual organization? , 2013, Cognition.

[24]  A. Majid,et al.  Odors are expressible in language, as long as you speak the right language , 2014, Cognition.

[25]  Hitoshi Sakano,et al.  Neural map formation in the mouse olfactory system , 2014, Cellular and Molecular Life Sciences.