| 研究課題/領域番号 |
22K00015
|
|---|
| 研究機関 | 国際教養大学 |
|---|
研究代表者 |
|
|---|
| 研究期間 (年度) |
2022-04-01 – 2025-03-31
|
| キーワード | artificial intelligence / scientific explanation / machine learning / philosophy of science / game of Go / data mining |
|---|
| 研究実績の概要 |
We continued to work on the analysis of cost of passing measure, and published an extended version of the paper. It includes the discussion of the measure of efficiency, fingerprinting of a game record database, and a more precise numerical characterization of game stages.
We did engineering work on the analysis software: changing the visualization library and separating the analysis tools from the Go engine and game management modules.
Further (originally unplanned) research was done on the algebraic automata theory analysis of games. This makes the definition of ground truth in game worlds precise and thus determines the available room for knowledge growth.
Started work on a new theory of explanation based on the idea of compatible operations (algebraic homomorphisms).
|
| 現在までの達成度 (区分) |
現在までの達成度 (区分)
3: やや遅れている
理由
Due to the unforeseen problems with the game record database (the rule sets and komi settings are not consistent) the historical analysis is slower than expected.
The best practices survey has been rescheduled due to the extra work on the algebraic game theory.
Regarding the spending, I have received generous funding from the University of Waterloo, thus there was no need for using the budget for my travel.
I had an accepted talk scheduled for the 1st International Go Studies Conference, but my presentation was cancelled last minute; the real reasons never disclosed. This did not affect the progress of the project directly, but psychologically it was damaging.
However, despite the minor setbacks and reorganizations, there is no reason to think that the project will not finish on time.
|
| 今後の研究の推進方策 |
Applying the theory of explanation based on morphic relations (as in algebra) to the game of Go. This will address the question, what is a good explanation and how can we create them from the non-explanatory but high-precision AI output. This is the focus of this project: verbalizing AI knowledge for human understanding. We will develop the algebraic/category theoretical ideas in concert with a scholarly study of the most recent literature on scientific explanation.
Finishing the historical game analysis with semi-automated (partially manual) detection and correction of rule sets for game records. We plan to create summary visualizations for a large number of games.
Finishing the best practices survey and detecting any deviations between current practice and our scientific recommendation.
|
| 次年度使用額が生じた理由 |
Conference travels and/or research visits e.g., to Nihon Ki-in, or the RC visiting AIU for intensive research meetings.
Maintaining (and possibly extending) the compute server farm for the historical game analysis.
Books for the scholarly study of scientific explanations and other project-related publications.
|
