Database Semantics for Talking Autonomous Robots

Abstract

Database Semantics (DBS) models the cycle of natural language communication as a transition from the hear to the think to the speak and back to the hear mode (turn taking). In contradistinction to the substitution-driven sign-based approaches of truth-conditional semantics and phrase structure grammar, DBS is data-driven and agent-based. The purpose is a theory of semantics for an autonomous robot with language. Propositions are content in DBS, instead of denoting truth values (Sects. 1–3). Content is built from the semantic kinds of referent, property, and relation, which are concatenated by the classical semantic relations of structure, i.e. functor-argument and coordination. To enable reference as an agent-internal cognitive process, language and nonlanguage contents use the same computational data structure and operation kinds, and differ mostly in the presence vs. absence of language-dependent surface values. DBS consists of (i) an interface, (ii) a memory, and (iii) an operation component. (The components correspond roughly to those of a von Neumann machine (Neumann 1945): the (i) interface component corresponds to the vNm input-output device, the (ii) memory (database) component corresponds to the vNm memory, and the (iii) operation component performs functions of the vNm arithmetic-logic unit.) The interface component mediates between the agent’s cognition and its external and internal environment, represented as raw data provided by sensors and activators (Sects. 4–7). The data of the agent’s moment by moment monitoring are stored at the memory’s now front. As part of the on-board control unit, the now front is the location for performing the procedures of the operation component, resulting in content.