We found that the human error rate in recognition of individual handwritten digits is 2.37%. This differs somewhat from two prior studies , .
Assigning the development of a poker-playing agent as a group project allows flexibility with respect to the topics and techniques typically covered in an introductory Artificial Intelligence course. A poker agent project also provides students the experience of 'authentic' AI research, due to the status of poker as an 'unsolved' problem in AI. Despite this… (More)
We established human performance in recognition of handwritten ZIP codes taken from the standard CEDAR database. We expect that the result will serve as a benchmark for machine performance in recognition of handwritten ZIP codes.