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Robotics has been considered as one of the five key technology areas for defense against attacks with weapons of mass destruction (WMD). However, due to the mass impact nature of WMD, failures of counter-WMD (C-WMD) missions can have catastrophic consequences. To ensure robots' success in carrying out C-WMD missions, we have developed a novel verification framework in providing performance guarantees for behavior-based and probabilistic robot algorithms in complex real-world environments. We cannot assume the luxury of a do-over; we must get it right the first time.

A framework to use machine learning techniques to generate rhythm action game stages from music

End-user interaction with machine learning based systems will result in new usability challenges for the fields of human computer interaction and machine learning. With machine learning systems becoming more and more prevalent, it is important that systems are properly designed in a user-centered manner. In order to address these challenges, the most relied upon usability inspection method-the heuristic evaluation-must be adapted for the unique end-user experiences that interactive machine learning presents. This project introduces ten heuristics for interactive machine learning.