UT Austin will be undertaking research on how robots can build competency models of their perception algorithms.

Cooney goes on, "With Fun LoL DARPA is looking for information about mathematical frameworks, architectures, and methods that would help answer questions such as: What are the number of examples necessary for training to achieve a given accuracy performance? What are important trade-offs and their implications? How close is the expected achievable performance of a learning algorithm compared to what can be achieved at the limit? What are the effects of noise and error in the training data? What are the potential gains possible due to the statistical structure of the model generating the data?"