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Comments by Joe Joyce

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Board games and aging[Subject Thread] [Add Response]
Joe Joyce wrote on 2019-11-27 UTC

This item is an unknown type!
It belongs to categories: Orthodox chess, 
It was last modified on: 2003-01-05
 By Fergus  Duniho. Game Courier. PHP script for playing Chess variants online.[All Comments] [Add Comment or Rating]
Joe Joyce wrote on 2019-08-27 UTC

Thank you. I appreciate it


Joe Joyce wrote on 2019-08-17 UTC

This completed game from Game Courier has errored out. Can it be recovered? Thanks, Joe

Almost Grand, a very modest variant[Subject Thread] [Add Response]
Joe Joyce wrote on 2018-12-18 UTC

Hi, HG! Thanks for the reply. Grin, I agree Grand Chess et al is a very immodest variant. But then Christian is the Ralph Betza of abstracts. He is the one who makes the distinction between variants of chess and variant chesses. And if FIDE wasn't so firmly enshrined in the psyche of the West, that would be a distinction with very little to no meaning. But as it is, make one little change, you are a heretic, and your audience size goes down at least 5 orders of magnitude.

I looked at Elven, and read some of the comments. If you don't mind my saying so, I think it would make a nice partner to Hannibal in a site tournament. It has that power that most here like, and has the kicker of the Chu Shogi Lion, a moderately terrifying piece which is rather unknown here, isn't it? Hmm, if I were to introduce that piece, I'd start by pairing it with my Lemurian hero and shaman, and Greg has a piece (griffin?) that has a similar movement to the hero... heh, one of the problems I have in discussing chess variants is that it gets me thinking of variant designs. Anyway, apparently I can claim Almost Grand as a very modest variant of Grand Chess, and even make a play for Almost Capa. And with that last, I can make the claim I seem to be pretty good at finding the obvious. ;D

Merry Christmas, all, and I hope your Chanukah was happy!


This item is a game information page
It belongs to categories: Orthodox chess, 
It was last modified on: 2017-12-02
 By Kevin  Pacey. Hannibal Chess. Chess with added Modern Elephants (ferz-alfil compound) on 10x8 board.[All Comments] [Add Comment or Rating]
Joe Joyce wrote on 2018-12-18 UTC

Thank you, Kevin, and Ben is right, I do occasionally push the boundaries of chess a bit more than most, and also the definitions. To me, Hannibal is about the minimum acceptable change for a game. It adds a simple shortrange piece and changes the board minimally, just enough to fit the colorbound pair. The idea is minimal, the play is excellent. I meant it about this being a decent tourney game. It's straight-up hardnosed chess, no gimmicks.

Almost Grand, a very modest variant[Subject Thread] [Add Response]
Joe Joyce wrote on 2018-12-18 UTC

If you read what Christian Freeling has said about Grand Chess, you might buy the argument that Grand Chess is one of the most excellent modest variants. Late night ideas - am writing a reply about Hannibal Chess, and got sidetracked to a slight variant of Grand Chess which I will have to exorcise before I can go to sleep. (Sorry, Kevin, I'll finish your reply tomorrow. ;) In considering what Christian thinks about his design, I came back once again to the idea that the piece set is not complete until you use the 3 king + rook/bishop/knight pieces also. So Almost Grand replaces the queen with the centaur (N+K), the archbishop with the dragon bishop (B+K), and the chancellor with the dragon rook (R+K), and all else is as Grand. This army is a little weaker than Freeling's, mostly from losing the ability to leap over adjacent pieces. Clearly it works for all the Carrera-Capa variants, and might actually help those games a little by toning down the power of the queen equivalents plus losing the archbishop's ability to checkmate without the aid of any other piece. I admit that after playing Grand Chess, playing Carrera-Capa made me feel claustrophobic!

Now this is such an obvious idea someone must have done it before. Can anyone point me to such a game?


This item is a game information page
It belongs to categories: Orthodox chess, 
It was last modified on: 2017-12-02
 By Kevin  Pacey. Hannibal Chess. Chess with added Modern Elephants (ferz-alfil compound) on 10x8 board.[All Comments] [Add Comment or Rating]
Joe Joyce wrote on 2018-12-12 UTCGood ★★★★

This is a very nice-playing modest variant. I've greatly enjoyed my games of it. I can absolutely recommend this game as an excellent variant tournament choice. It gets a lot of mileage out of a pair of fairly simple changes. The initial set-up is excellent; it gives good play. The weak piece is a very nice choice, and provides a nice companion/foil for the bishop and knight.

4D chess with Allen Pan and Phisics girl (aka Diana)[Subject Thread] [Add Response]
Joe Joyce wrote on 2018-11-08 UTC

Interesting video. The game in the video falls between our two games, Ben, in its approach to 4D. Personally, I think the 3D board is too gimmicky; I rarely like boards that don't display rotational or reflection symmetry. And I think that the 2D 'double grid' 4x4x4x4 board would make it easier easier to see moves in my version, but for yours, Ben, the 3D-style boards might just be better... what do you or anyone with experience think?

[Subject Thread] [Add Response]
Joe Joyce wrote on 2018-09-07 UTC

"Myers-Briggs was, in its original essence, the work of a salty and extremely committed mother-in-law who needed to understand what the hell was going on with her daughter’s romantic choices."

This topic has come up before on this site, so I thought this might be of interest.

This item is a play-by-email page
It belongs to categories: Orthodox chess, 
It was last modified on: 2007-09-15
 By Joe  Joyce. Falcon King Chess. A shortrange variant on an 8x8 board featuring a pair of royal Falcons.[All Comments] [Add Comment or Rating]
Joe Joyce wrote on 2018-07-15 UTC

I don't know why they have code. I never use any code - I can't. Instead I erase all of it. I always make presets that are just dumb boards and pieces. When they were made, they worked. Whjen I look at what I put in, there's only this in the introduction box:

<p>This is a pair of experimental games featuring entirely shortrange pieces. There are two presets, ShortChess and Falcon King. ShortChess uses the standard FIDE king as the single royal piece with a Falcon "queen"; Falcon King has a pair of royal Falcons on each side.
<a href="/play/pbm/play.php?game%3DShortChess%26settings%3DfutC1">
<a href="/play/pbm/play.php?game%3DFalcon+King+Chess%26settings%3DfutC2">
  <h3>Falcon King Chess

This is what you get when you try to get the presets:

Syntax Error on line 287
The function BIL has not been defined.        
287 for to fn join #piece L #from

Something is off[Subject Thread] [Add Response]
Joe Joyce wrote on 2018-05-15 UTC

Another game that no longer exists is

Great Shatranj joejoyce-cvgameroom-2018-94-353 1 day, 0 hours ago

Something is off[Subject Thread] [Add Response]
Joe Joyce wrote on 2018-05-13 UTC

I couldn't get into the site for some hours this (Sunday) afternoon. I got blank pages repeatedly. I tried going into active games where I was to move, and got odd error messages and extremely truncated pages. Finally I was able to move in a game a while ago. When I tried again just now, the site came up fine. I use Mozilla Firefox.

This item is an unknown type!
It belongs to categories: Orthodox chess, 
It was last modified on: 2015-04-10
 Author: Fergus  Duniho. Game Courier Ratings. Calculates ratings for players from Game Courier logs. Experimental.[All Comments] [Add Comment or Rating]
Joe Joyce wrote on 2018-04-27 UTC

Stupid question: Could you rate wins as +2 and losses as -1, and would that help?

Piece names (What piece is this?)[Subject Thread] [Add Response]
Joe Joyce wrote on 2018-04-24 UTC

Thanks, Greg! Grin, kind of embarrassing when you've played the game... Gryphon is certainly a better name than knight cannon or knight catapult, which I was considering. George, thanks for reminding me about the names trebuchet and catapult. Clearly I remembered them unconsciously, It was bugging me. It is such a nice piece someone should have used it somewhere, but that is true of many pieces. And it does fit very nicely in The ShortRange Project, George, filling one of the many holes in the piece lists. Note it hits 16 squares, with a max range of 3, falling neatly between pieces like the FAN, WDN, DWAF hitting 16 squares with a max range of 2 and the AF+AF and DW+DW pieces, hitting 16 squares with a max range of 4. Or conversely, between the A+F and D+W, range 3, footprint 12, and the A+/-F and D+/-W, range 3, footprint 20.

Where does thre Gryphon rank in power in the above group of pieces?

Joe Joyce wrote on 2018-04-24 UTC

Apologies, George, but HG is right about the "H", if not the "D". :)  The WNH seems like a very nice knight companion in larger variants. I was actually wondering what might make a nice activator piece for 4 knights. The WNH popped into my head maybe 12 hours later. Thanks, both of you.

Anybody ever seen a WNH anywhere before?

Joe Joyce wrote on 2018-04-24 UTC

Is there a name for the WNH piece?

This item is an unknown type!
It belongs to categories: Orthodox chess, 
It was last modified on: 2015-04-10
 Author: Fergus  Duniho. Game Courier Ratings. Calculates ratings for players from Game Courier logs. Experimental.[All Comments] [Add Comment or Rating]
Joe Joyce wrote on 2018-04-23 UTC

Actually, I found that when I played competitively a few years ago, the more different games I played, the better I played in all of then, in general. This did not extend to games like Ultima or Latrunculi, but did apply to all the chesslike variants, as far as I can tell.

This item is a game information page
It belongs to categories: Orthodox chess, 
It was last modified on: 2018-04-23
 By Joe  Joyce. Granlem Shatranj. This is a mash-up of Grand Shatranj & Lemurian Shatranj with a 3 moves/player turn option.[All Comments] [Add Comment or Rating]
Joe Joyce wrote on 2018-01-13 UTC

Thanks, Kevin. Man added to the piece descriptions. I've used a specific, systematic iconology to represent how the shatranj-style pieces I use move, which can be found in the chess variants wiki under Joe's strange notation. Once you know the symbols, you can tell exactly how the piece moves from the icon. Grin, it covers everything except the man.

The test game I'm currently playing is moving a little slow. The center is developing differently on both sides, but nothing is really happening on the 2 wings. I think this game really wants 3 moves per player-turn. The combination of short-range pieces and limited command areas plus not allowing any piece to move twice in a turn keeps the game from getting crazy, but does allow a much faster game and a different one, as ther is no great incentive to develop the wings in the beginning of the game that I can see. The restricted 3-move option should provide a decent and non-chaotic game.

This item is a game information page
It belongs to categories: Orthodox chess, 
It was last modified on: 2002-05-28
 By Ralph  Betza. Chess with Different Armies. Betza's classic variant where white and black play with different sets of pieces. (Recognized!)[All Comments] [Add Comment or Rating]
Joe Joyce wrote on 2018-01-06 UTC

A minor quibble here about board size: it can be considered a mutator. There are variants which propose placing an 8x8 standard chess set-up in the middle of a 10x10 or 12x12 board. This does change the game a fair bit. Now, with a 10x8, you can use it a few ways. You might have a file a rook can step to on either side of the standard 8x8 set-up, or you could 'play the long way' and set up with 6 rows of 8 squares empty between the 2 sides, or even move both sides up 1 square, so they ar the standard distance apart, but there is an extra row behind each side. Circular boards have long been used, also, for example. But what you are really doing here is examining how board geometry affects play and affects the utility of various pieces (eg: on a Byzantine circular board, bishops are nerfed and rooks are enhanced. In other words, you're playing Chess with Different Boards.

Game Courier[Subject Thread] [Add Response]
Joe Joyce wrote on 2018-01-05 UTC

Got this when I saved a test game preset:

Your settings have been saved as DoubleGOmove1. To access these settings for a game, use this URL:

FAILED to REPLACE the row for this settings file in the GameSettings table. This may affect the information available about your settings file, and this failure should be reported to Fergus Duniho for correction. Tell him that the following line of SQL failed:

REPLACE INTO GameSettings(Game, Settings, Redirect, Author, Rules, Coded, Lastmod) VALUES ('Double GOmove', 'DoubleGOmove1', '', '', '', 0, 1515093310)

Alpha Zero plays chess[Subject Thread] [Add Response]
Joe Joyce wrote on 2017-12-16 UTC

"Aurelian Florea wrote on 2017-12-15 EST


I will make sure that machine learning does invade the chess variants world. :)!"

Good! Make me an opponent for Macysburg and its bigger (and smaller) relatives. ;) I need a good opponent to learn from.

"V. Reinhart wrote on 2017-12-15 EST

I think it's pretty much hopeless for anyone to argue that humans can win against computers in any type of game. Our only chance of winning a game is to play it before it gets studied by computers. So people like @Aurelian and @JoeJoyce will need to stay busy inventing new games faster then people like @GregStrong and @HGMuller can program this stuff!!"

I actually agree that AI on good hardware will generally outperform humans, eventually. And for games, I suspect the AI will start with something very like AlphaZero as described by HG Muller below. If not, it will be something better.

I do think, however, people grossly underestimate the size of the game space AZ must evaluate each turn for a more complex abstract, or just how much the possibilities expand with each additional ply investigated. The ‘best moves’ often depend on enemy intentions and *exactly* where each piece winds up in 2 – 3 turns, and may depend on which order you move your 50 or 100 or 250… pieces each turn.

"H. G. Muller wrote on 2017-12-15 EST

Note that AlphaZero is not just a neural network. It is a tree search guided by a NN, the NN being also used for evaluation in the leaf nodes. The tactical abilities are mainly dependent on the search. The NN is just good at deciding which positions require further search to resolve the tactics."

The key to how well the AI does on commercially available machines in a few years (under reasonable assumptions) depends heavily on just how good the neural net is “at deciding which positions require further search to resolve the tactics,” I believe. That may be enough of a handicap for humans for a little while.


Aurelian Florea wrote on 2017-12-16 EST

Actually I'm more in it for the mathematics of chess variants…

Grin, that comment may have been a mistake! I would truly like to understand just why the Command and Maneuver games I’ve designed work as well as they do. In considering the introductory scenario A Tale of Two Countries: Intro, the first thing I noticed was that there are an amazing number of essentially equivalent moves available each turn, of which the player can only make 8. Which 8? It’s a small game, 12 x 24, with only 36 pieces/side at start, and while there are replacements and reinforcements arriving during the game, 36 units is probably the largest size either army will ever be.


I totally accept for the sake of argument that the AI will be a tactical genius in Tale, but I question the strategic elements because it seems to me that future game states are indeterminate, because while the AI may/will make the best tac moves this turn, the human probably won’t. So how does the AI ‘guess’ the game state in 2 or 3 turns, say 3 – 6 plys (player turns) deep?


In Macysburg, the situation is probably worse, at 32 x 32 and 84 pieces/side, all able to move each turn, arriving in 4 even-sized groups around the edge of the board over 20 turns, with ‘rally” allowing 1/3rd of the captured pieces to be returned to the board.  


The pieces dance back and forth seeking advantage. Where a piece is on the next turn is often difficult to determine. And ‘combat,’ standard chess capture, is totally dependent on the exact locations of every piece. While you can figure out/guess some of what your opponent might do in reply to your current moves, you really can’t do predictions accurate enough to put your pieces in motion for a couple turns and expect to have them all positioned right to demolish the enemy without taking equal losses.


For humans, there’s a very strong indeterminacy that provides the necessary ‘fog of war’ in the game. Why would the AI do so much better at penetrating that indeterminacy?


When I considered the paths - world lines - of the pieces in Tale, I saw that they were chaotic in the same sorts of ways that mathematical chaos is explained for the non-mathematical mind. Some strategically or tactically located pieces of terrain act as strange attractors, pulling in pieces from all over the board. Pieces that start off next to each other may all follow the same general (parallel) world line or split apart to end up almost anywhere on the board. And starting with the same board configuration, you may get some similar world lines from game to game, or wildly divergent ones.


Agreed, just in this description, I’ve given handles with which to attack the problem, and good statistics helps - a lot, I’d imagine. But isn’t there some sort of limit to how accurate a projection an AI could make? If AIs could truly predict the future, there’d be an awful lot of very rich programmers, no? ;) Doesn’t the strong presence of chaos wash away the ability to predict accurately? And isn’t that the AIs best weapon?


Finally, just for the record, the games I’m describing I’ve designed only because I wanted to play them, not to defeat computer players. I’ve long been fascinated by the idea of a  genuine, workable fusion of chess and war games, and for humans at least, these games work well, according to the people who managed to play them with me (some discussion on boardgamegeek.)

Joe Joyce wrote on 2017-12-15 UTC

I agree, Aurelian. I think it's obvious that neural nets could 'easily' (with much hardware, time, and $$) play games like I've described at human level, and possibly a bit beyond. My point is that there are far too many indeterminacies for even the best neural nets to successfully predict game states (ie: what the opponent, or even the AI itself, will do in a couple of turns) for the software to consistently outperform the best humans or human teams. The game tree for even a specific game of Macysburg (a 32x32 abstract strategy war game riff on the Battle of Gettysburg during the American Civil War) is ridiculous. If AlphaZero depends in part on the exact board configuration, that can/does change significantly game to game. And predicting future game states does not work except in the most limited of circumstances. The best the AI can achieve is a generalized knowledge of how terrain affects movement and combat. It can apply those rules very well in limited situations and be a brilliant tactician, but so can humans. The AI clearly has the potential to be better at tactics, but how much better? And I don't think the AI can be significantly better in strategy without teaching us more about strategy. I think that people find it very hard to understand the total range of possibilities. The game starts with about 42 pieces on the board, all of which can move every turn, if they have a nearby leader. And there are 3 reinforcement turns which bring in another ~42 pieces each time. Excpect to have ~100 pieces maneuvering in the middle of the game. Exactly where each type of piece stands each turn, the exact order in which they are moved, exactly where terrain is in relation to each piece, as well as what the terrain is - different pieces get different effects - determine what attacks can be made each turn, and changing any of those conditions changes what happens *each turn*. I maintain that unless quantum computers work exactly as advetrised, the AI *cannot* effectively predict future game states to any overwhelmingly useful degree. Thus, based on monte carlo statistical approaches, such Ais can be at best only marginally better than the best humans/human teams.

Joe Joyce wrote on 2017-12-14 UTC

Aurelian, I've read the first part of the paper V. Reinhart linked a bit after our comments. My math was always bad, but I think this is a relevant paragraph in the paper:

Instead of an alpha-beta search with domain-specific enhancements, AlphaZero uses a general-purpose Monte-Carlo tree search (MCTS) algorithm. Each search consists of a series of simulated games of self-play that traverse a tree from root s root to leaf. Each simulation proceeds by selecting in each state s a move a with low visit count, high move probability and high value (averaged over the leaf states of simulations that selected a from s) according to the current neural network fθ. The search returns a vector π representing a probability distribution over moves, either proportionally or greedily with respect to the visit counts at the root state.

I believe that it would take a truly remarkable neural net to significantly outperform all humans either individually or as teams playing as a general staff, because the sheaves of probability explode from each potential group of moving pieces interacting with each different board or even different entry squares or entry times presented.

Let me offer you a link to a website under construction that steps through the first "day" of a purely combinatorial abstract strategy combat simulation, which includes 24 sequential "daylight" turns alternating between blue and red, and a lesser number of "night" turns to finish all combat, separate the 2 sides, "rally" troops - return 1/3rd of each side's losses to the owning player to drop by friendly leaders. Marked reinforcements come in between turns 8 & 9 (4 turns for each side) on their assigned entry areas, are unmarked and move normally from the start of the next daylight turn. The sequence above is repeated again, with on-board sides each being reinforced twice, once on daylight turns 29/30 and again on 39/40. After a second night, a 3rd day with no reinforcements is played. If none of the 3 criteria for victory has been achieved by either player, both lose. Otherwise, a victor or a draw is determined. (please wait for it to load - thanks! Said it's under construction!)

Note terrain blocks movement and is completely variable. There are a handful of elements I put in each version of the scenario, a "city" of around 10 squares in the center of the board, a "mountain in the northwest quadrant of the board, a "forest" in the south, a "ridge" running from NE to SE of the city's east edge, a light scattering of terrain to break up and clog up empty areas on the board, and a dozenish entry areas. Nothing need be fixed from game to game. How does even a great neural net do better than any human or team every single time? There are far too many possibilities for each game state, and truly gigantic numbers of game states, in my semi-skilled opinion.

Joe Joyce wrote on 2017-12-12 UTC

It's true that humans don't handle ever more complex calculations, but it's also true that humans are good at pattern recognition. Further, a highly complex situation where there are many many equivalent moves, one that effectively precludes good forecasting of enemy replies, would, I think, prevent Alpha Zero from becoming significantly better than all humans. In a purely combinatorial abstract strategy military or military-economic conflict game, where mathematical chaos is how the massively multimove game 'works' in a military sense, there isn't a good way to project future game states, and this I believe would keep a calculating machine from becoming significantly better than all humans to the extent that a human or human team could win against the AI. This is what I'm curious about. Is there a ceiling to ability in complex enough abstracts and does this mean humans can win against the best machines in such games?

Joe Joyce wrote on 2017-12-11 UTC

AlphaZero is a neural net which learns by playing against itself, starting with random moves and working up to a rating of over 3300, iirc. It runs on some very fancy hardware, so  its learning time is misleading. It played millions of games against itself to learn Go. I'm curious about just what it learns when it's teaching itself a game. How dependent is it on the exact board geometry and each player moving only one (or a few) pieces per turn? If the game is a very large (~1000 - 10,000 squares or more) massively multi-move abstract strategy war game with a board that can change between games, does that sort of thing make any significant difference, or merely add some time to the AI learning process?

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