You might be interested in delta-bar-delta algorithm for adapting the
gain size (0.99 in your example)
http://www.cs.ualberta.ca/~sutton/papers/sutton-92a.pdf
Lukasz Lew

On Thu, Jun 26, 2008 at 19:58, Jason House <[EMAIL PROTECTED]> wrote:
> I tendto like exponentially weighted moving averages when I need a fading
> memory. That keeps storage simple, updates fast, and nearly the same effect
>
> i.e.
> wins = 0.99*wins + latest_result
> sims = 0.99*sims + 1
>
> Sent from my iPhone
>
> On Jun 26, 2008, at 2:40 PM, "Ivan Dubois" <[EMAIL PROTECTED]> wrote:
>
>> This same topic already occured on the list some time ago.
>> I think the idea is to "forget" older results. For exemple you can compute
>> the win rate based only on the last 500 simulations. Older information may
>> not be up to date and will not help much because 500 simulations is enough
>> to compute an accurate winrate.
>> The problem is that you have to store the result of 500 simulations at
>> each node. I think some people reported that it does indeed increase the
>> strength of their program.
>>
>> ----- Original Message ----- From: "Peter Drake" <[EMAIL PROTECTED]>
>> To: "Computer Go" <computer-go@computer-go.org>
>> Sent: Wednesday, June 25, 2008 5:48 PM
>> Subject: [computer-go] UCB/UCT and moving targets
>>
>>
>>> UCB (and hence UCT) would treat the following sequences of wins (1)  and
>>> losses (0) the same:
>>>
>>> 01010101010101010101010101010101
>>> 00000000000000001111111111111111
>>> 11111111111111110000000000000000
>>>
>>> Clearly, it would be better to favor the second sequence, because that
>>> move has done more for us lately. Because the tree is growing, the  values
>>> of the moves are moving targets.
>>>
>>> Has anyone done any work dealing with this phenomenon, e.g., somehow
>>> giving more weight to more recent playouts?
>>>
>>> Peter Drake
>>> http://www.lclark.edu/~drake/
>>>
>>>
>>>
>>> _______________________________________________
>>> computer-go mailing list
>>> computer-go@computer-go.org
>>> http://www.computer-go.org/mailman/listinfo/computer-go/
>>
>>
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>
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