TY - JFULL AU - Michael Harre and Terry Bossomaier and Ranqing Chu and Allan Snyder PY - 2010/6/ TI - Strategic Information in the Game of Go T2 - International Journal of Computer and Information Engineering SP - 948 EP - 954 VL - 4 SN - 1307-6892 UR - https://publications.waset.org/pdf/11390 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 41, 2010 N2 - We introduce a novel approach to measuring how humans learn based on techniques from information theory and apply it to the oriental game of Go. We show that the total amount of information observable in human strategies, called the strategic information, remains constant for populations of players of differing skill levels for well studied patterns of play. This is despite the very large amount of knowledge required to progress from the recreational players at one end of our spectrum to the very best and most experienced players in the world at the other and is in contrast to the idea that having more knowledge might imply more 'certainty' in what move to play next. We show this is true for very local up to medium sized board patterns, across a variety of different moves using 80,000 game records. Consequences for theoretical and practical AI are outlined. ER -