NEW! Get all Tourneybot Results from the new Board here: http://www.fibsboard.com/tourneybot-results/
Started by diane, June 26, 2010, 01:50:48 AM
Quote from: sixty_something on July 01, 2010, 09:14:24 PMthe better player minimizes his error rate in so doing he optimizes his 'luck' potential yielding the impression the better player is luckierthan less skilled opponents
Quote from: dorbel on July 05, 2010, 08:58:01 AMThis figure coincides with my own shorter studies of matches played between me and gbots on fibs. I have broken the study down into games rather than matches.
Quote from: dorbel on July 05, 2010, 08:58:01 AMHowever the better player, which in my study is at least occasionally me, gets the positive luck more often.
Quote from: pck on July 05, 2010, 01:29:23 PMThe densities in the second graph should be symmetrical around zero instead of showing the biases they do.
Quote from: pck on July 05, 2010, 01:29:23 PMSo what do you think? Have you shown with this that total luck does not tend to zero in the long run if the skill difference between the players is large? Or have you shown that gnu's calculation of luck is defective? You're obviously aware of the problem or you wouldn't have included that "if" above.
Quote from: sixty_something on July 05, 2010, 03:41:52 PMnow, boomslang, would you consider conducting another experiment to test another aspect of of this theory? i believe that the more moves (or games) analyzed the more the calculated "luck" differential will diverge between a better player and a less skilled player probably up to some limit .. while 42,000 moves may be a large enough sample to have reached such a limit, it may not be .. so, if it isn't too time consuming, how would that last graph look after say 100,000 moves or more? any idea where that limit may be or if there is a limit at all?finally, has anyone yet directly addressed diane's original question and really defined how the "luck" calculation really works?
Quote from: boomslang on July 05, 2010, 11:50:27 PMI included the 'if' because of Diane's remark about bots appearing lucky.
Quote from: boomslang on July 05, 2010, 11:50:27 PMWhy do you think that? I think they should have an average of zero (because luck tends to zero in the long run), but they cannot be symmetrical because the better player will be more likely to be really unlucky than to be really lucky. (In other words, it has virtually no chance to be really lucky because its opponent gives away too many equity and it had won the game/match already. Remember, these graphs are from the situation expert vs newbie.)
Quote from: boomslang on July 05, 2010, 11:50:27 PMNot sure what you mean... What I meant to explain with this quote is the source of the 'dip' in the graphs of Zorba and me.I included the 'if' because of Diane's remark about bots appearing lucky. When a bg player simply looks at whether or not a bot had a positive total luck and draws his conclusion on that -- and I think a lot of players do that -- he will indeed see a lucky bot more often than an unlucky bot. It is however unfair to conclude that bots are lucky in the long run, because of the negative skewness of the distribution of luck during a game or match for the bot.
Quote from: boomslang on July 05, 2010, 11:50:27 PMAnd yes, that means that I think the asymmetry of the distributions are not artefacts caused by GNUbg's inconsistency in evaluating luck and skill.
Quote from: sixty_something on July 05, 2010, 03:41:52 PMall i am saying is "the nature of backgammon", as boomslang says, and the nature of the "luck" calculation yield "the impression the better player is luckier" .. boomslang's graph number 4 seems to directly support this .. indeed it appears to may be more than an impression, but it is a slippery slope as we have seen to attempt to equate pure theoretical luck with "luck" calculations .. i think all of us who play bots significantly more powerful than we are have repeated first hand experience that bots just seem too damn lucky - don't we? i would contend that this perception is merely a reflection f what boomslang's experiment has shown
Quote from: David McCulloughWriting is thinking. To write well is to think clearly. That's why it's so hard.
Quote from: dorbel on July 09, 2010, 08:59:34 AMHowever, I don't recall ever seeing this research anywhere else and kudos to these guys for adding something new to the game right here on fibs. Applause, applause.
Quote from: dorbel on July 09, 2010, 08:59:34 AMIt is important to understand that what we mean by "luck" LUCK, usually winning a game with a joker, is something different [than calculated "luck"] and something that on average will be equal in the long run. Other than that, I am not sure how understanding what is going on will help us to play better! A good play is still a good play, same as it ever was.
Quote from: dorbel on July 09, 2010, 08:59:34 AMThe contributions of boomslang in particular, as well as pck and Zorba, have contributed to our understanding of what bots mean by "luck" and why superior players get the "luck" more often than not. ...However, I don't recall ever seeing this research anywhere else and kudos to these guys for adding something new to the game right here on fibs. Applause, applause.
Quote from: sixty_something on July 09, 2010, 04:14:14 PMsomething i'd especially like to see are definitions of key terms and phrases .. for example,LUCK - pure luck such as that we see when rolling fair dice which we all agree is theoretically equal regardless of skill"luck" - the calculated expression of equity gain or loss for an individual player resulting directly from the roll of the dice in a given situationare those definitions complete and acceptable?can we concurr LUCK and "luck" are two independent entities with different properties?
Quote from: sixty_something on July 09, 2010, 04:14:14 PMcan we further state that boomslang's work provides convincing evidence that in the long run a significantly better player tends to accumulate more "luck" than the less skilled player?
Page created in 0.266 seconds with 28 queries.