Natural language acquisition by a robot

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“... nothing reveals our ignorance about a phenomenon more clearly than an attempt to define it in constructional terms.” (W. Grey Walter, The Development and Significance of Cybernetics) We present a model of language acquisition which demonstrates that considerable language competence can be acquired without presupposing innate linguistic factors. Vague or magical properties are avoided by describing the model as a design for a robot using clearly defined algorithms and mechanisms which can be simulated or constructed. Described first is the development of a simplified semantic system using a minimum of cognitive apparatus operating in a restricted environment. This works in conjunction with an algorithm to develop grammatical competence. No innate grammatical knowledge is needed; only interaction with an environment and a native speaker of the language is required. Grammatical competence is portrayed in terms of a new syntactic model, whose power is demonstrated by a game “simulation” in which the players make connections allowed by the syntactic rules to generate and parse English sentences. The paper closes with a second game which simulates the robot and its “parent” by a team of human players. This simulation shows how the robot develops its semantic and syntactic systems through its experience in the world.