MCx analysis stub
This game (LG)
Download JTwixt file
On 2020-01-31 at 23:13,
Here is the evaluation and the principal variation for each move.
On 2020-02-01 at 23:56,
Thanks so much! But this is most curious. If TB evaluated its position as below 0 on the first move, why didn’t it swap?
On 2020-02-02 at 01:02,
A fair question! Quite possibly it should, but instead there is a special bit of code that overrides all the neural net smartness for specifically the first move and the swap move.
On 2020-02-02 at 12:51,
Well it’s your code, you are welcome to do whatever you want, but IMO the stronger the bot is, the more value it has as a teaching tool. Other players might prefer you go the other way, and offer a dumbed down version. I suggest, for a TwixtBotSlow version which will take a few hours per move, that you adjust its initial moves and swap choices to match its evaluations? Maybe you could build up a swap map for the top left quadrant, spending hours on each initial move. I’m always finding more work for you, sorry.
On 2020-02-03 at 01:27,
I don't really trust the evaluations to be on the right side of 0, so it's not obvious to me that using the evaluation to decide swap is a win. I mean, it might be, but it might not, you know? Anyway, the swap rules I have now are a result of having the bot self-play itself a few dozen times with each possible start point.
On 2020-04-01 at 22:51,
I'm obviously way out of touch with recent developments. Did we never used to understand anything about openings? Do we understand now? Do people think that the Twixt Bot openings are good, or that TwixtBot is so good that it can overcome them?
On 2020-04-03 at 18:56,
TwixtBot is feeling out positions, tracing all the way to the end, until it is satisfied a move is strong. Its only sense of intuition is pattern recognition from a neural net, recognizing patterns of links and pegs. It lacks the capacity for abstract thinking, so it has no opening move theory, like humans do. I think the consensus is that its opening moves are generally weak, but its play gets stronger very quickly, so your window to gain the upper hand is very short, and maintaining the upper hand is difficult.
I am not sure what we can learn from TwixtBot about opening moves. One thing it often does is tactical moves right from the start, which has traditionally been considered a rookie mistake. However, if its position is strengthened in the battle, maybe it is a valid approach. You just have to be insanely good at tactical moves to feel confident starting that way.
I think there is an opportunity to develop an opening move AI competition. The task is to program an AI that handles Twixt opening moves, but can hand the game over to TwixtBot at any time. The default opponent is a null AI that just hands it over to TwixtBot right away. Any AI that can beat the null AI more than 50% of the time in a statistically significant number of games will have proven TwixtBot's AI to be deficient in opening move theory.
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