Chai et al. present a greedy As natural language capable robots and other agents become algorithm which uses a subset of the Givenness Hierarchy more commonplace, the ability for these agents to understand to resolve a wide array of referential expressions, but this truly natural human speech is becoming increasingly approach operates under a closed-world assumption (Chai, important. What is more, these agents must be able to understand Prasov, and Qu 2006). Kollar, Tellex et al. present Generalized truly natural human speech in realistic scenarios, Grounding Graphs, which instantiate probabilistic in which an agent may not have full certainty in its knowledge graphical models based on the structure of incoming NL utterances, of its environment, and in which an agent may not have and use those models to resolve references (Tellex full knowledge of the entities contained in its environment.

A linear architectural model of cortical simple cells is presented. The model evidences how mutual inhibition, occurring through synaptic coupling functions asymmetrically distributed in space, can be a possible basis for a wide variety of spatiotemporal simple cell response properties, including direction selectivity and velocity tuning. While spatial asymmetries are included explicitly in the structure of the inhibitory interconnections, temporal asymmetries originate from the specific mutual inhibition scheme considered. Extensive simulations supporting the model are reported.

A linear architectural model of cortical simple cells is presented. The model evidences how mutual inhibition, occurring through synaptic coupling functions asymmetrically distributed in space, can be a possible basis for a wide variety of spatiotemporal simple cell response properties, including direction selectivity and velocity tuning. While spatial asymmetries are included explicitly in the structure of the inhibitory interconnections, temporal asymmetries originate from the specific mutual inhibition scheme considered. Extensive simulations supporting the model are reported.

A linear architectural model of cortical simple cells is presented. The model evidences how mutual inhibition, occurring through synaptic coupling functions asymmetrically distributed in space, can be a possible basis for a wide variety of spatiotemporal simple cell response properties, including direction selectivity and velocity tuning. While spatial asymmetries are included explicitly in the structure of the inhibitory interconnections, temporal asymmetries originate from the specific mutual inhibition scheme considered. Extensive simulations supporting the model are reported.