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HELEN: Using Brain Regions and Mechanisms for Story Understanding to Model Language as Human Behavior

A new cognitive model is presented for large-scale representation of episodic situations and for manipulating these representations using the model's innate natural language processing mechanisms. As formulated, and implemented in part, the purpose of the model seeks to attain basic child level cognitive behavior of situational understanding. This includes general domain learning, by assigning internally- relevant, though subjective, value to common experience (input situations), and by being taught how to analyze/synthesize component representations of those input situations. Ultimately this will allow it to learn and autonomously create situations with meaning from those components to best fit problem situations. The current model is written in C++ as a visual interface and is implemented as a story understander with question answering and language generation capability.