Using an Episodic Memory Module for Pattern Capture and Recognition

We propose an episodic memory-based approach to the problem of pattern capture and recognition. We show how a generic episodic memory module can be enhanced with an incremental retrieval algorithm that can deal with the kind of data available for this application. We evaluate this approach on a goal schema recognition task on a complex and noisy dataset. The memory module was able to achieve the same level of performance as statistical approaches and doing so in a scalable manner.