Abstract
How spatial language, important to both cognitive science and robotics, is mapped to real-world scenes by neural processes is not understood. We present an autonomous neural dynamics that achieves this mapping flexibly. Neural activation fields represent and spatially transform perceptual information. An architecture of dynamic nodes interacts with these perceptual fields to instantiate categorical concepts. Discrete time processing steps emerge from instabilities of the time-continuous neural dynamics and are organized sequentially by these nodes. These steps include the attentional selection of individual objects in a scene, mapping locations to an object-centered reference frame, and evaluating matches to relational spatial terms. The architecture can respond to queries specified by setting the state of discrete nodes. It autonomously generates a response based on visual input about a scene.
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References
Amari, S.I.: Dynamics of pattern formation in lateral-inhibition type neural fields. Biological Cybernetics 27(2), 77–87 (1977)
Barsalou, L.W.: Perceptual symbol systems. Behavioral and Brain Sciences 22(04), 577–660 (1999)
Carlson, L.A., Logan, G.D.: Attention and spatial language. In: Itti, L., Rees, G., Tsotsos, J.K. (eds.) Neurobiology of Attention, ch. 54, pp. 330–336. Elsevier Academic Press (2005)
Guadarrama, S., Riano, L., Golland, D., Gohring, D., Jia, Y., Klein, D., Abbeel, P., Darrell, T.: Grounding spatial relations for human-robot interaction. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (2013)
Knauff, M.: Space to reason: A spatial theory of human thought. MIT Press, Cambridge (2013)
Lipinski, J., Schneegans, S., Sandamirskaya, Y., Spencer, J.P., Schöner, G.: A neurobehavioral model of flexible spatial language behaviors. Journal of Experimental Psychology. Learning, Memory, and Cognition 38(6) (2012)
Logan, G.D., Sadler, D.D.: A computational analysis of the apprehension of spatial relations. In: Bloom, P., Peterson, M., Nadel, L., Garrett, M. (eds.) Language and Space, ch. 13, pp. 493–529. MIT Press, Cambridge (1996)
Lomp, O., Zibner, S.K.U., Richter, M., Rañó, I., Schöner, G.: A software framework for cognition, embodiment, dynamics, and autonomy in robotics: cedar. In: Mladenov, V., Koprinkova-Hristova, P., Palm, G., Villa, A.E.P., Appollini, B., Kasabov, N. (eds.) ICANN 2013. LNCS, vol. 8131, pp. 475–482. Springer, Heidelberg (2013)
Pylyshyn, Z.W.: The imagery debate: Analogue media versus tacit knowledge. Psychological Review 88, 16–45 (1981)
Richter, M., Sandamirskaya, Y., Schöner, G.: A robotic architecture for action selection and behavioral organization inspired by human cognition. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2457–2464 (2012)
Sandamirskaya, Y., Schöner, G.: An embodied account of serial order: How instabilities drive sequence generation. Neural Networks 23(10), 1164–1179 (2010)
Schneegans, S., Schöner, G.: Dynamic field theory as a framework for understanding embodied cognition. In: Calvo, P., Gomila, T. (eds.) Handbook of Cognitive Science: An Embodied Approach. Perspectives on Cognitive Science, pp. 241–271. Elsevier (2008)
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Richter, M., Lins, J., Schneegans, S., Schöner, G. (2014). A Neural Dynamic Architecture Resolves Phrases about Spatial Relations in Visual Scenes. In: Wermter, S., et al. Artificial Neural Networks and Machine Learning – ICANN 2014. ICANN 2014. Lecture Notes in Computer Science, vol 8681. Springer, Cham. https://doi.org/10.1007/978-3-319-11179-7_26
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DOI: https://doi.org/10.1007/978-3-319-11179-7_26
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