A Multimodal Connectionist Architecture for Unsupervised Grounding of Spatial Language

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A Neurorobotic Experiment for Crossmodal Conflict Resolution in Complex Environments * (2018, background): “g, in terms of forming (or learning) multisensory representations from heterogeneous sensor data [2] or modelling the development of sensorimotor skills in embodied agents [3].”
Emergence of multimodal action representations from neural network self-organization (2017, background): “For instance, Vavrečka and Farkaš (2014) presented a connectionist architecture that learns to bind visual properties of objects (spatial location, shape and color) to proper lexical features.”