Print-and-Play: I’m willing to print card sheets for students enrolled in this course, and I have the tools and can teach the skills necessary to create your own playable set. Enrolled students can email me and I’ll be glad to help create a physical copy of the game in office hours. The only cost to you if you want an easy shuffling experience would be to purchase clear plastic card sleeves, specifically at least 120 sleeves of this size. Other options are listed here. (All money and points can be easily tracked with a free app such as Score Counter for Android. If you find a good iOS one to recommend, please let me know.
Guenther Rosenbaum Windows application: There is a free, fan-made, single-player vs. AI-only Saint Petersburg application (see email for link) by Guenther Rosenbaum that can be played using cross-platform software called Wine. Professor Presser has generously taken the time to pre-install it as an easy-to-launch application on all lab machines (“Saint Petersburg”), but you can also install this on your own personal computer.
Board Game Arena: Saint Petersburg is still a popular-enough game to have regular players online at Board Game Arena 21 years after its release. To initiate a game, one must have a subscription, but anyone can play for free who is willing to wait for an open table (or an invitation from a paid subscriber). There were 505 games in progress at time of writing.
Strategy discussion can be found at the BGG forum.
Class 2 ():
Preparation: play of SP, observing significant features for decisions
Preparation: Moodle work log, experiment with (1) new objective function (e.g. logistic regression win probability breaking ties with score difference), and/or (2) generate better play data for learning from self-play of flat MC player. Note: Feel free to speed collection of play data by having the flat MC player collect fewer samples per action.
Decision Trees
Class 6 ():
Preparation:
Bias-Variance Tradeoff, Training and Test Sets, Decision Tree Regularization, Decision Tree Ensembles
Class 7 ():
Preparation: Moodle work log, complete Competition 1 entry
Competition 1 entry due via email
Class 8 ():
Preparation: Presentation of Competition 1 entry
Presentation and discussion of entries
Class 9 ():
Preparation: Moodle work log,
Gradient-Boosted Decision Trees
Class 10 ():
Preparation:
Class 11 ():
Preparation: Moodle work log,
Class 12 ():
Preparation:
Class 13 ():
Preparation: Moodle work log,
Class 14 ():
Preparation: Moodle work log, complete Competition 2 entry
Competition 2 entry due via email
Class 15 ():
Preparation: Moodle work log,
Class 16 ():
Preparation:
Class 17 ():
Preparation: Moodle work log,
Class 18 ():
Preparation:
Class 19 ():
Preparation: Moodle work log,
Class 20 ():
Preparation:
Class 21 ():
Preparation: Moodle work log, complete Competition 3 entry
Competition 3 entry due via email
Class 22 ():
Preparation:
Class 23 ():
Preparation: Moodle work log,
Class 24 ():
Preparation:
Class 25 ():
Preparation: Moodle work log,
Class 26 ():
Preparation:
Class 27 ():
Preparation: Moodle work log,
Class 28 ():
Preparation:
Final: Final report and Moodle work log due Sunday, December 7th, 4:30PM.
