A Sensory-Motor Linguistic Theory for Artificial Cognitive Systems

We propose a linguistic approach to model human activity. The Human activity language (HAL) consists of kinetology, morphology, and syntax. Kinetology, the phonology of human movement, finds basic primitives for human motion (segmentation) and associates them with symbols (symbolization). This way, kinetology provides a symbolic representation for human movement that allows synthesis, analysis, and symbolic manipulation. Kinetology also has applications to compression, decompression, and indexing of motion data. The morphology of a human action is related to the inference of essential parts of the movement (morpho-kinetology) and its structure (morpho-syntax). In order to learn the morphemes and their structure, we present a grammatical inference methodology and introduce a parallel learning algorithm to induce a grammar system representing a single action. In practice, morphology is concerned with the construction of a vocabulary of actions to aid an artificial cognitive system. The syntax of human activities involves the construction of sentences using action morphemes. Sets of morphemes represent simultaneous actions (parallel syntax) and a sequence of movements is related to the concatenation of activities (sequential syntax).