Combinatorial Game Theory Workshop E. Berlekamp (Berkeley), M. Mueller (University of Alberta), R. J. Nowakowski (Dalhousie University), D. Wolfe (Gustavus Adolphus College). June 18 to June 23, 2005 A main aim of the workshop was to bring together the two camps, mathematicians working in combinatorial game theory and computer scientists interested in algorithmics and Artificial intelli- gence. The Workshop attracted a mix of people from both communities (17 from mathematics, 16 from computer science and 2 undergraduates) as well as a mixture of new and established researchers. The oldest was Richard Guy, turning 90 in 2006 and the youngest was in 3rd year University. There were attendees from Europe, Asia as well as North America. The Workshop succeeded in its primary goal and more. New collaborations were struck. There was quick dissemination and evaluation of major new results and new results were developed during the Workshop. Part of the success was due to the staff and facilities at BIRS. The facilities at BIRS were appreciated by all the participants. The main room allowed lectures to mix computer presentations with overheads and chalkboard calculations. (No prizes for guessing which community used which technology.) The coffee lounges and break away rooms allowed dis- cussions to continue on, in comfort, until late in the night. Our thanks go to all the staff who made the stay such a wonderful experience and to the BIRS organization for hosting the workshop. The elder statesmen of the community, Berlekamp, Conway, Fraenkel and Guy, all took active roles in the proceedings. The first three gave survey talks on various topics and all were involved in discussions throughout the days and the evenings. The younger (established) generation were represented by the likes of Demaine, Grossman, M¨uller and Siegel. As befits a workshop on combinatorial games, games were invented, played and analyzed. Philoso- phers Football (Phutball) was much in evidence. There was a Konane tournament played over three evenings. Much effort went into attempting an analysis of Sticky Towers of Hanoi, a game invented at the Workshop by Conway, spearheaded by Conway and the youngest attendee, Alex Fink. There were many representatives of the Go community quite a few of whom had never met each other. Collaboration is very important in this community. For example, David Wolfe presented a progress report on work of G. A. Mesdal on a class of partizan splitting games, answering questions first raised over 30 years ago. Mesdal is a joint effort of eleven co-authors from North America and New Zealand. Eight of the eleven attended the workshop and the number of co-authors had risen to twelve by the time the Workshop ended. In the end, between the talks and the discussions, there was simply too much to absorb in such a short time. The talks, surveys and several consequent papers are slated to appear as (tentatively titled) Games of No Chance 3 in the MSRI book series. 1 2 All the presentations were at a high standard and all had lively discussions during and after the time allotted. Some highlights were: Conway’s talk on lexicodes; Berlekamp’s overview Today’s View of Combinatorial Game Theory; and Fraenkel’s What hides beyond the curtain separating Nim from non-Nim games; Demaine’s talk on Dyson Telescopes and Moving Coin Puzzles also showed the complexity in some very new and some very old puzzles. However the highlights were the reports by: 1. Plambeck on a breakthrough in the analysis of impartial mis`ergames; 2. Siegel on extending the analysis of loopy games; 3. Friedman and Landsberg on applying renormalization techniques from physics to combinatorial games—this paper was both controversial and thought provoking and lead to the most discus- sions, including ones on the nature of truth and of proof; 4. Nakamura on the use of ‘cooling by 2’ to determine the winner in ‘races to capture’ in Go. One of the goals of the Workshop was to bring together researchers from mathematics and computer science. This was one of the talks that helped bridge the gap and engendered much discussion. The 30 minutes allotted to the talk was too short, and most participants stayed an extra hour (into the dinner-time) so as to hear the details. All of these were very new, very important results, produced only months before the Workshop. 1: Mis`ere Games: On page 146 of On Numbers and Games, in Chapter 12, “How to Lose When You Must,” John Conway writes: Note that in a sense, [mis´ere] restive games are ambivalent Nim-heaps, which choose their size (g0 or g) according to their company. There are many other games which exhibit behaviour of this type, and it would be very interesting to have some general theory for them. Questions about the analysis of mis´ereimpartial octal games were raised in [3, 6] and no good general analytical techniques have been developed apart from finding the genus sequence [3]. (See [1, 22], see also [8, 20]). In his presentation, Plambeck provided such a general theory, cast in the language of commutative semigroups. The mis`ereanalysis of a combinatorial game often proves to be far more difficult than its normal play version. In fact it is an open question (Plambeck) if there is a mis´ereimpartial game whose analysis is simpler than the normal play version and there is no know way of analyzing mis´ere partizan games ([15], Problem 9). To take a typical example, the normal play of Dawsons Chess was solved as early as 1956 by Guy and Smith [16], but even today, a complete mis`ere analysis has not been found. Guy tells the story [15]: “[Dawsons chess] is played on a 3 × n board with white pawns on the first rank and black pawns on the third. It was posed as a losing game (last-player-losing, now called mis`ere) so that capturing was obligatory. Fortunately, (because we still don‘t know how to play Mis`ere Dawsons Chess) I assumed, as a number of writers of that time and since have done, that the mis`ereanalysis required only a trivial adjustment of the normal (last-player-winning) analysis. This arises because Bouton, in his original analysis of Nim [5], had observed that only such a trivial adjustment was necessary to cover both normal and mis`ereplay...” But even for impartial games, in which the same options are available to both players, regardless of whose turn it is to move, Grundy & Smith [14] showed that the general situation in mis`ereplay soon gets very complicated, and Conway [6], (p. 140) confirmed that the situation can only be simplified to the microscopically small extent noticed by Grundy & Smith. In Chapter 13 of [3], the genus theory of impartial mis`ere disjunctive sums is extended signifi- cantly from its original presentation in chapter 7 (How to Lose When You Must) of Conways On Numbers and Games [6]. But excluding the tame games that play like Nim in mis`ere play, theres a remarkable paucity of example games that the genus theory completely resolves. For example, 3 the section Mis`ereKayles ([3], pg 411) promises, “Although several tame games arise in Kayles (see Chapter 4), wild games abounding and well need all our [genus-theoretic] resources to tackle it...” However, it turns out Kayles wasn‘t tackled at all. It was left to the amateur William L. Sibert to settle mis`ereKayles using completely different methods. One finds a description of his solution at end of the updated Chapter 13 in [4], and also in [22]. When normal play is in effect, every game with nimber G+(G) = k can be thought of as the nim heap k. No information about best play of the game is lost by assuming that G is in fact precisely the nim heap of size k. Moreover, in normal play, the nimber of a sum is just the nim-sum of the nimbers of the summands. In this sense every normal play impartial game position is simply a disguised version of Nim (see [3], Chapter 4, for a full discussion). Genera. When mis`ereplay is in effect, nimbers can still be defined but many inequivalent games are assigned the same nimber, and the outcome of a sum is not determined by nimber of the summands. These unfortunate facts lead directly to the apparent great complexity of many mis`ere analyses. Nevertheless progress can be made. The key definition, taken directly from [6], now at the bottom of page 141: In the analysis of many games, we need even more information than is provided by either of these values [G+ and G−], and so we shall define a more complicated symbol that we call the Go-value or genus. This is the symbol g.g0g1g2 ... + − − − where g = G (G), g0 = G (G), g1 = G (G + 2), g2 = G (G + 2 + 2), ..., where, in general, gn is the G−-value of the sum of G with n other games all equal to [the nim-heap of size] 2. At first sight, the genus symbol looks to be an potentially infinitely long symbol in its exponent. In practice, it can be shown that the gis always fall into an eventual period two pattern. By convention, the symbol is written down with a finite exponent with the understanding that its final two values repeat indefinitely. Evidently the exponent of a genus symbol of a game G is closely related to the outcome of sums of G with all multiples of mis`erenim heaps of size two. The genus computations are intended to illustrate the complexities of a mis`ereanalysis when the only tools available to be applied are those described in Chapter 13 of Winning Ways.