TRACX is a new model of sequence learning. It is a connectionist autoassociator model which fits a wide range of phenomena from the infant statistical learning and adult implicit learning literature. TRACX outperforms PARSER (Perruchet & Vintner, 1998) and the simple recurrent network (SRN, Cleeremans & McClelland, 1991) in matching human sequence segmentation on existing data. This simulator is written entirely in Javascript and runs locally in your browser. A short summary of the algorithm can be found here and more details of the model can be found in:
French, R. M., Addyman, C., & Mareschal, D. (2011). TRACX: A recognition-based connectionist framework for sequence segmentation and chunk extraction Psychological Review, 118(4), 614–636. doi:10.1037/a0025255 [pdf - 872k]