[HN Gopher] Mastering the Game of Stratego with Model-Free Multi...
___________________________________________________________________
Mastering the Game of Stratego with Model-Free Multiagent
Reinforcement Learning
Author : aklein
Score : 100 points
Date : 2022-07-11 15:32 UTC (7 hours ago)
(HTM) web link (arxiv.org)
(TXT) w3m dump (arxiv.org)
| spywaregorilla wrote:
| Stratego is an odd choice I feel. Evaluating it must be really
| hard. A significant chunk of the game is just trying to remember
| which unit is which of the things you've seen so far. Which
| humans generally can't do very well but machines can do easily.
| Beating hand crafted bots is good.
|
| Can expert humans beat the hand crafted bots? I'm guessing no.
| Also, what's stratego like without the hidden units? Is that...
| hard?
| boringg wrote:
| I don't think you are that familiar with how good Stratego is
| played. It isn't strictly a memorize where your opponents units
| are. There's a significant degree of bluffing and posturing.
| thekiptxt wrote:
| To the extent that machines can't replicate. If I place my
| hand on a piece that's illegal to move, feign that I'm
| reconsidering, and then move a different piece, then my
| opponent may suspect that the originally touched piece may be
| moved.
|
| How can I use these 200 IQ moves against a bot?
| elcomet wrote:
| This does not apply when playing machines. Like facial
| expressions or gestures do not apply when playing poker
| with machines.
| spywaregorilla wrote:
| It isn't strictly about memorizing where your opponents are,
| but having a perfect memory would be an enormous advantage,
| the point of being an entirely different game imo.
| ghaff wrote:
| Yes, playing it as a kid I remember one pretty common thing
| to do was to make movements that made it easy for your
| opponent to get confused about whether a piece was that
| known piece or something else. Not the whole strategy but
| take that piece out and you definitely change the game I
| would think relative to typical human play. Especially in
| the context of it normally being more of a kids game.
| treis wrote:
| Seems like it would be easy to test. See how the AI does
| when revealed pieces stay revealed compared to a standard
| game.
|
| Also, given this is online competitive play likely that a
| significant portion of top human players are cheating and
| have aides to keep track of pieces.
| spywaregorilla wrote:
| > Seems like it would be easy to test. See how the AI
| does when revealed pieces stay revealed compared to a
| standard game.
|
| It would effectively need to be a different AI to use
| that information. And what does it play? Humans? Other
| AI?
|
| > Also, given this is online competitive play likely that
| a significant portion of top human players are cheating
| and have aides to keep track of pieces.
|
| That's a great point. It may even be condoned in some
| circles.
| TemplateRex wrote:
| The pace in online games is too fast (4s per move
| usually, with a 12m buffer) to use pen and paper aides.
| Short of having some sort of screen-scrabbing AI-tool
| that auto-labels pieces as they are revealed (doable by a
| decent programmer, but Stratego is no poker, there's no
| money in it), I think it's safe to assume top-level
| players don't cheat. Top-level play in live tournaments
| has a high correlation with top-level online play as
| well.
| EthanHeilman wrote:
| Most good players of stratego have perfect memory of all
| revealed information during a game. That's basic table
| stakes for playing, like memorizing the dictionary is for
| scrabble or memorizing openings for chess. It isn't very
| hard to do, since most moves don't reveal the value of
| piece and those moves to do reveal a piece tend to led to
| the destruction of that piece within a move or two. A
| computer isn't going to have an advantage there.
| Imnimo wrote:
| From the paper:
|
| > Successes in the game have been limited, with artificial
| agents only able to play at a level comparable to a human
| amateur, see e.g. (14-20).
| riku_iki wrote:
| It could be because no one seriously tried to build
| competitive AI player.
| Buttons840 wrote:
| _I think_ the best human players can beat the best computer
| players in Stratego. Thus, Stratego is an excellent choice.
| janosett wrote:
| You might consider reading the linked abstract: "... Stratego
| has been a grand challenge for the field of AI for decades, and
| existing AI methods barely reach an amateur level of play."
| spywaregorilla wrote:
| Sounds like bullshit to me. I'm not convinced. Here's a paper
| from 2021 that suggests as much. It's hard, sure, but it's
| also not really seriously explored.
|
| > Compared to other games like Chess and Go, not much work
| has been done on creating an AI agent for Stratego. As such,
| the available literature is far and few between, and mostly
| consists of bachelor's and master's theses. In fact, most
| agents created for Stratego are largely undocumented or
| closed-source, making it difficult to effectively ascertain
| exactly which particular methods and techniques have been
| applied and how effective they were.
|
| edit: the claim about bots not beating humans appears to
| hold, but I'm not convinced its just shoddy bot quality.
| JoshCole wrote:
| Just to give a sense of hardness, Stratego's game tree is
| infinitely larger than Go's game tree, because in imperfect
| information you select a continuous strategy vector over
| action space whereas in Go you select a discrete action.
| Meanwhile Stratego is also infinitely more complex than Go
| because in Go there are less moves with every move, but in
| Stratego moves don't monotonically decrease the remaining
| game length.
|
| Beyond those two infinities of greater complexity, Stratego
| is imperfect information, so it is played relative to the
| infostate, not the state. In Stratego there are thirty
| three pieces with unknown information on the first move. We
| can definitely get a lower upper bound by applying
| abstraction via domain knowledge, but just so I don't have
| to deal with the complexity I'll state that there are at
| most 8683317618811886495518194401280000000 different states
| associated with the infostate of your first move.
| Meanwhile, on your first move in Go, you are in at most 1
| state.
|
| In practice though the average length of a game of Go is
| ~200ish, the average length of Stratego ~400ish.
|
| Much like chess, I would expect optionality to be an
| important strategic consideration in Stratego. So branching
| factors are likely selected for such that they get higher
| by good agents. In contrast to something like Go, the
| branching factor would tend to diminish over time.
|
| Mostly sharing this because I think most people are bad at
| reasoning about complexity - our mind is really good at
| making complex things seem simple and simple things seem
| complex because we can actually deal with the complexity of
| simple things in their full complexity but dealing with the
| full complexity of the complicated is intractable. I
| imagine a lot of people's mind latch onto the things like
| "we get information so playing well means memorization" and
| don't pay as much focus to the dizzying complexity; but
| playing well isn't memorizing. Playing well is playing
| perfectly according to your uncertainty and it just so
| happens that as part of doing that you sometimes reduce
| your uncertainty by scouting.
| spywaregorilla wrote:
| This is all technically true, but it's also misleading I
| feel. Chess and Go have a lot of states, and you need all
| of them. The entropy of the games are enormous. Move that
| bishop and the significance of every piece on the board
| could change. Stratego has verrrryy low entropy. You can
| only move one piece one space at a time aside from
| scouts. You can also enter scenarios where the game just
| simplifies on some dimensions immensely to which some
| fairly dumb algorithms can win the game. If the enemy
| loses their top dude and their spy, your top guy is
| invincible against anything that has ever moved, which
| isn't victory assured but its probably relatively easy to
| write an ai to win from that point on.
|
| Maybe this is just me but when I thought about stratego
| I'm pretty sure I only thought about a few units at a
| time. Moving all of them is a bad idea because of bombs
| anyway. Your mental model of the game does not consider
| the state of units in the back row of either side. It
| probably doesn't even consider all of the units in the
| front.
|
| I also suspect a lot of optimal play is just doing dumb
| shit back and forth to force your opponent into making
| the more aggressive move in a lot of cases without
| technically forfeiting which most humans likely wouldn't
| do but ai would like to do if not constrained otherwise.
|
| But I agree a simple tree search on possible moves is
| unlikely to work very well until the end game.
| JoshCole wrote:
| If I'm understanding you correctly, you're saying that
| the rules of Stratego let you apply an abstraction rule
| which drastically simplifies the game. I agree you can do
| this. I think this point is remarkably similar to the
| technique of blueprint abstraction.
|
| Of course, we ought to be focused on the situations which
| lead to these nice situations - which leads us back to
| the imperfect information situations which lead to those
| positions we can reason about.
|
| Interestingly, you can invert your point and get a
| similar rule more generally. The trick is to backward
| induction on the abstracted category transitions. So your
| point is actually so valid that is valid even in
| situations where your examples don't apply. I hope you
| can see I'm strong manning here. I agree with you that
| this should be done and is critical to making things
| tractable.
|
| There is an issue though, at least in the generalized
| case, which is that perfect information is much easier
| than imperfect information.
|
| See, in perfect information games when you do the
| backward induction step you actually just flat out solve
| the game. Meanwhile, in imperfect information games, this
| backward induction step merely makes solving the game
| more tractable. Chess endgames are the backward induction
| version of your forward induction from the rules
| abstraction, but the abstraction rule is so hard to
| determine we wouldn't usually think of it that way.
| Notice that chess is hard enough that we don't have
| endgame tables that go all the way back to the start of
| the game? Yet the average game length in Stratego is
| hundreds of moves longer and there are more then double
| the number of pieces.
|
| I still think your point is right and someone who pushes
| hard enough in this direction would manage to tackle the
| complexity. So I basically agree with you. But if you
| take standard approaches like counterfactual regret
| minimization and throw it at the game without adjusting
| them for the fact that the problem is "hard" then they
| just wont terminate.
| spywaregorilla wrote:
| I guess I have two points. Perfect information stratego
| is not a hard game at all. There's still a lot of moves
| one can make but perfect play is easy to calculate. Near
| perfect play is probably easy enough even for an amateur
| player. My gut says many games will converge on this
| state (early) if you have an unbeatable piece.
|
| Without perfect information, the number of states is
| still mostly a red herring, because the differences
| between the states are immaterial. The moves aren't super
| important. If you decide to move frontline unit A against
| the frontline unit on the opposite side of the field,
| there may be several moves between that but you've only
| made one noteworthy decision. Could be bad intuition. I
| think a more abstract model here would do better and be
| far simpler with some minor tactical move prioritization
| or whatever.
| TemplateRex wrote:
| The best available bot that is also mentioned in the paper, is
| Probe. Expert humans will score the same as DeepNash against
| Probe. The best humans have no trouble recalling every piece
| that moved, and the square it originated from. Top-level play
| usually has very few moved pieces (since they are vulnerable to
| your opponent's general once your own marshal gets revealed),
| so memory is important but typically not the main bottleneck.
| spywaregorilla wrote:
| > Top-level play usually has very few moved pieces (since
| they are vulnerable to your opponent's general once your own
| marshal gets revealed), so memory is important but typically
| not the main bottleneck.
|
| Interesting. Is top level play... boring? Stratego doesn't
| have a lot of nuance to positional advantaging aside from
| moving forward or back, and while I'd imagine there's
| stalemate rules, there's probably a lot of nothing moves to
| dance around getting super minor and uninteresting
| advantages. Is that a correct statement?
| TemplateRex wrote:
| It depends on player attitudes. The maneuvering is simpler
| than in chess or even checkers, although you can have very
| intricate multi-piece pincers around the lakes. Most top
| players however tend to be quite aggressive, sacking majors
| or even colonels to expose the opponent's top two pieces,
| while at the same time having their counter attacks ready.
| Typically there are 3 simultaneous battles for each of the
| 3 alleys. But, yeah, as in chess, there can be bloodless
| draws or fortress positions where neither wants or can make
| headway.
| dr_orpheus wrote:
| > A significant chunk of the game is just trying to remember
| which unit is which of the things you've seen so far
|
| While this does get hard the further you go in the game, a
| think a more significant portion of the strategy is trying to
| predict newly moving units based on what is happening in the
| game. i.e. I just took a 7 unit with my 8. And now my opponent
| is coming straight towards me with a unit from elsewhere. Is it
| a 9 or 10, is it a bluff to drive me off, to drive me in to a
| spot where the actual 9 or 10 is waiting?
| spywaregorilla wrote:
| Computers are better at such problems.
| aidenn0 wrote:
| Did they renumber the pieces? In the set I played as a kid a
| scout was 9 and a Marshall was 1...
| wakamoleguy wrote:
| Yes, around 2000 they swapped the numbers. Most recent
| versions treat the Spy as 1 and Marshal as 10. Classic
| versions ranked the Marshal as 1 and Scouts as 9, with the
| Spy designated as S.
| andruby wrote:
| I bought a set to play with my kids and felt like
| something was off but couldn't really recall. Thanks!
| miiiiiike wrote:
| Got a copy of Stratego (one of the old-style ones with descending
| rank, as pleases the gods) so I could show my board game loving
| girlfriend one of my favorite games from when I was a kid. She
| hated it.
| LionTamer wrote:
| Seeing the paper title gave me so much nostalgia for playing
| Stratego as a kid, that was always my favorite Board game. Glad
| to see I'm not the only one who used to love that game, few of
| my friends growing up played it.
| jrussino wrote:
| Did you still enjoy it? I loved playing this game with my Dad
| when I was a kid and I'm wondering if it still holds up.
| TedDoesntTalk wrote:
| Played it recently with a 12 year old boy. He loves it.
| jasone wrote:
| It held up for me. I played a lot of Stratego with family and
| friends as a kid, but there was one friend in particular who
| routinely wiped the battlefield with my pieces. I couldn't
| understand how he so consistently beat me, and as an adult I
| was able to 1) reason more deeply about the game, and 2)
| quickly learn deeper strategy from the Internet. As a result,
| the game is even richer now to me than it was in the 1980s.
| evouga wrote:
| I mean. Stratego is a great game; I had a lot of fun playing it
| at summer camps when I was a young boy. It's cool there's a good
| AI for it.
|
| But this result feels a bit anticlimactic in a world where AIs
| can already beat expert humans at go, six-player poker,
| Starcraft, ...
| 60secz wrote:
| These are interesting not because you're solving for a game,
| but because you're potentially partially solving a category of
| problem.
| goodside wrote:
| It's explained right in the abstract why Stratego is a more
| difficult game for AI than go or poker.
| TemplateRex wrote:
| You can view Stratego as the "Cartesian product" of a public
| information board game and an imperfection information "card"
| game. The board game has much simpler local tactics than e.g.
| chess or checkers, although whole board tactics where 2+ high
| pieces are trapping 1 lower piece defended by 1+ high piece
| are extremely complicated to reason about.
|
| The "card" game can be viewed as a form of Limit Poker. The
| bidding in poker is done with secret cards and public bets.
| In Stratego, you bet _with_ your secret pieces, so it 's more
| like a closed bid auction. But since there are only 10
| moveable ranks, the range of bluffs you can pull off is
| rather limited compared to e.g. No Limit Poker.
|
| Each of the "subgames" in itself are quite tractable for
| computers. But the numerical product of all public game
| states times the number of secret information states is
| humongous. Combine this with the fact that imperfect
| information game trees don't decompose as nicely as e.g.
| chess game trees, and computers will also not be able to
| divide-and-conquer their way out of the numerical complexity
| with brute force. Whereas humans can come a long way with
| heuristics.
| kzrdude wrote:
| How far did they get with Starcraft? Stratego should be a
| stepping stone to get there - it introduces imperfect
| information.
| confuseshrink wrote:
| Starcraft in the form of Alphastar worked in the sense that
| it could beat humans, at least in the short term. The problem
| with the whole technique is that they had to tether it to the
| human examples they had gathered in the form of a divergence
| loss.
|
| I haven't checked out the linked paper yet but if they
| managed to do something from first principles that would
| still be an interesting development.
| anonymoushn wrote:
| spywaregorilla left a good reply about Starcraft. In the
| games I watched, despite the AI being handicapped to use
| human-like levels of APM and human-like viewport management,
| it primarily fought using *clearly superhuman* blink stalker
| micromanagement. Stalkers with barely any health would
| typically survive engagements and get to re-engage when their
| shields were fully recovered. On the other hand, a human
| player managed to confuse the bot by repeatedly airdropping
| units in its base, picking them up, and dropping them
| elsewhere. The bot uselessly moved its mass of stalkers back
| and forth while losing many probes and buildings.
|
| Edit: After looking at some games again, the AI also benefits
| from precise target selection for the phoenix's graviton
| beam. A human player might take 3 phoenixes and a bunch of
| stalkers into a fight against an army containing 3 immortals,
| some sentries, some stalkers, and some zealots, and use
| graviton beam to pick up some mix of units including units
| other than immortals. The bot can pick up only the immortals.
| spywaregorilla wrote:
| It's very difficult to say. There are many cookie cutter
| strategies for RTS games and it's difficult to handicap the
| ai to note use its machine precision and quickness of
| thinking to just win everything on a tactical level. actions
| per minute handicaps are not nearly nuanced enough to capture
| this. Generally it seems that the absolute top humans are
| better than bots strategically but the execution to do so is
| really, really tough. And then of course there are dumb
| exploits because you find some dumb weakpoint than any sane
| human would quickly adjust their behavior for.
| warrenm wrote:
| I haven't played Stratego in decades!
|
| Loved it as a kid, though
| hervature wrote:
| I'm still trying to grok and implement the paper, but I studied
| AlphaGo/AlphaZero/MuZero during my PhD. The core contribution
| here is the Nash equilibrium component to imperfect information
| games using only self-play. Note, there is no MCTS being done in
| this paper. This differs from counter factual regret methods
| (like the most famous Poker AIs) because it does not need to
| compute for all possible "information sets" which makes it
| intractable for even sufficiently complicated poker variants. It
| should also be noted (as they do in the paper) that this is more
| incremental than methodologically innovative as AlphaGo. This is
| the AlphaZero step increment to NeuRD. As is my general critique
| with their previous papers, they generally omit many engineering
| details that prove to be very important. Here, they admit that
| fine-tuning is vitally important (one of the 3 core steps) but
| details are relegated to the supplementary materials. It also
| opens up the question of if this new "fine-tuned" policy still
| guarantees the Nash equilibrium which it obviously does not as
| some mixed strategies are going to have sufficiently small
| probability. I wish researchers would be more honest with "this
| is a hack to get things to work on a computer because neural
| networks have floating point inaccuracies". It doesn't ruin any
| of the theory and no one is going to hold it against you. But it
| causes all sorts of confusion when trying to reimplement.
| algo_trader wrote:
| > I'm still trying to grok and implement the paper, but I
| studied AlphaGo/AlphaZero/MuZero during my PhD
|
| What is the SOTA on solving non-adversarial (single player?)
| POMDPs? Are those considered to be much simpler problems?
| hervature wrote:
| POMDPs is exactly how one formalizes imperfect information
| games. This is where the concept of information sets comes
| from. To answer your question, any two player algorithm is
| going to apply to single player games as it is trivial to
| transform. For games like 2048, the "adversary" is simply the
| opposite of your outcome. For games where you are trying to
| maximize your score, this is the standard RL setting and any
| of the Atari algorithms (including MuZero) can be used.
|
| In case you are wondering about cooperative multi-agent
| games, I would check this group's publications: https://www.c
| s.ox.ac.uk/people/publications/date/Shimon.Whit...
| igorkraw wrote:
| It strongly depends on what type of structure you can assume
| and how expensive sampling is. Dreamerv2, agent57 on Atari,
| dreamerv2 and the generalized agent model trained on 600
| tasks by deepmind might be worth looking into for different
| approaches on pomdps, but you can do much better if you
| impose physics priors by e.g. using neural ODEs for the
| latent state modeling.
|
| POMDP just means "observations are not state" and that you
| need to use a stateful policy to infer the state somehow, but
| without further assumptions it's difficult to answer this
| question
| TemplateRex wrote:
| What I don't understand is why they don't try to make
| inferences about the opponent's private state. I get that the
| full Bayesian update is intractable, but some sort of RNN or
| LSTM should be able to produce pretty accurate estimates for
| the opponent's private info. And with self-play, you can train
| the deduction head of a NN by adding a KL-divergence between
| inferred and ex-post observed pieces. That would both make you
| guess better and also try and "jam" your opponent's inference
| by randomizing your own piece distribution.
| hervature wrote:
| This is an interesting avenue for future research. The reason
| why it is not as straightforward as you claim is because all
| inference is going to depend on your perception of their
| policy. That's why the Nash equilibrium is sought after
| first. Because you should assume your opponent is perfect
| until you start observing their suboptimal behavior that you
| can exploit. Additionally, you would also have to handle the
| meta part where the exploiting portion of the algorithm isn't
| itself being exploited by the opponent. Somehow, you should
| deviate slowly from the Nash equilibrium but revert quickly
| if the opponent is abusing your new strategy.
| TemplateRex wrote:
| But their NN already outputs a policy conditional on public
| and private info! Why not have a separate intermediate
| branch in the NN that is fed with the current estimate of
| private info (for both players) and outputs the policies
| (again for both players) _given those info estimates_?
| Wouldn 't it be possible to learn from that?
| hervature wrote:
| First, the neural network is taking the history of
| observations into account. We don't know what the NN has
| learned, but the NN is probably making some inference on
| likelihood of opponent piece locations. They haven't
| explicitly coded it to do that but it is difficult to
| imagine a human-level AI not doing this.
|
| Second, what you are suggesting is probably best done as
| a secondary process outside of learning the Nash
| equilibrium. If you knew an opponent's policy, you would
| need to recalculate your optimal counterplay for that
| specific policy. This is completely orthogonal to the
| goal of this paper which is to learn the Nash equilibrium
| through self-play alone.
| mensetmanusman wrote:
| Would it be interesting if the posted the approximate kWhr energy
| required to train?
| voidfunc wrote:
| I haven't played Stratego since I lost my board when I was in
| third grade and brought it to play during recess...
|
| Is there a good online version these days?
| hirundo wrote:
| When I was a kid I "won" a Stratego game with a non-move that my
| friend claimed was against the rules. So he claimed the win.
| Could I get an umpire's call here?
|
| The issue is that when considering my next move, I picked up the
| bomb piece, thought for a few moments, put it back down, and
| moved another piece. My friend then, assuming that I had just
| given away that it was _not_ a bomb, attempted to capture it, and
| lost the attacker.
|
| He claimed that it was illegal to pick up that piece and put it
| down again, although he had no objection until he learned that
| I'd tricked him. We had never previously announced or enforced a
| touch-it-move-it rule.
|
| So did I win that game or did he? That's not a question machine
| learning could answer.
| Swenrekcah wrote:
| You won. Deception is obviously a critical part of all warfare.
| yborg wrote:
| By that argument, the opponent rightfully won, because
| negotiation is also a critical part of warfare. He got his
| opponent to give away a tactical battlefield victory on the
| basis of mutually agreed ground rules.
|
| Of course, dissatisfaction with such outcomes has often
| resulted in further wars.
| aidenn0 wrote:
| Official ISF tournament rules[1] say:
|
| > Touching one of his own pieces does not oblige a player to
| move it.
|
| It also says:
|
| > Psychology, bluff and misleading manoeuvres are considered
| important aspects of Stratego. Bluffing consists of all verbal
| communication (talking) or non-verbal communication (acting,
| mimic or feign) which is intended to mislead your opponent. All
| forms of bluff are allowed at any time during the game, unless
| prohibited by any other rule. Abuse will be considered
| unsporting behaviour and can be penalized accordingly.
|
| So I think you won.
|
| 1: https://isfstratego.kleier.net/docs/rulreg/isfgamerules.pdf
| toast0 wrote:
| I agree
|
| > 5.2 Moving
|
| > Flag and Bombs are never moved (For the definition of
| ,,move": see chapter 6).
|
| Chapter 6 shows the sequences of moves, and then Chapter 7
| says:
|
| > A move is made when:
|
| > a piece is released on another square than the starting
| one, or
|
| > a player touches an opponent"s piece with one of his own
| pieces or with the hand in which his own piece is held.
|
| So if the piece was picked up and replaced on the starting
| square, it was not moved, and that's fine.
|
| On the other hand, these rules incorporate some other rules
| by reference which includes:
|
| > The bombs and the flag may never be moved and therefore
| remain in the same place throughout the duration of the game
|
| A bomb hasn't exactly remained in the same place if it's been
| picked up, has it?
| TemplateRex wrote:
| In actual live game play, none of the top players use such
| kids' ploys as touching bombs pretending to be moveable
| pieces. Actual game play wouldn't change if the one touch
| move rule from chess or checkers were to be introduced.
|
| The main thing the rules guard against is accidentally
| tripping over your opponent's or your own pieces.
| Especially during time trouble, it sometimes happens that
| you drop a piece. If your opponent reveals < 4 of your
| pieces, you can exchange all of them with any other of your
| pieces. With >= 4 "accidents", it's an automatic forfeit.
| If you tip over your opponent's flag, he is entitled to 3
| swaps (may or may not be bombs).
| aidenn0 wrote:
| I always wondered if the pieces could be redesigned to
| have a strong bias towards landing "face down" when
| bumped; I've definitely accidentally revealed pieces
| before when making a quick move.
| boringg wrote:
| Hmm that you picked up the piece might have been an infraction.
| I constantly touch the bomb pieces but I don't lift them off
| the ground which implies that they can move.
|
| Tough call - glad that you are still carrying this from your
| childhood though. I would wager that you won but through
| borderline cheating. Still not sure TBH
| milesskorpen wrote:
| If you're playing seriously, I think if you touch a piece you
| need to move it.
| HWR_14 wrote:
| You won because "He claimed that it was illegal to pick up that
| piece and put it down again, although he had no objection until
| he learned that I'd tricked him."
|
| I think "touch-move" is perfectly valid to enforce, but you
| waive your right to do so once you move after that. If someone
| touches a piece in chess, then moves another piece, you don't
| get to go all the way until you're mated and then say there was
| an error you should have won on.
|
| And if you touch an illegal to move piece, I would say there
| the penalty would probably be revealing the bomb (or that it is
| immobile), not forfeiture of the game.
| Imnimo wrote:
| Wow! I did exactly the same thing as a kid. I though I was
| sooooo clever.
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