...the paper by Madani et al:
www.labri.fr/perso/gimbert/stageM2/*madani*.pdf



>
> Thanks Steve for your answer.
>
> 1) One-player randomized games (paper by Madani et al)
> For the paper by Madani et al, they work on unobservable problems; there is
> a graph, some transitions are labelled with actions (e.g. just binary
> actions), and some others are labelled with probabilities (rational
> probabilities are ok, so there's no problem for encoding this). The instance
> also contains a rational number c, and the question is "is there a sequence
> of actions leading to acceptance with probability at least c". The
> undecidability result is then a classical undecidability result, by
> reduction to the halting problem for Turing machines.
>
> 2) Two-player games
> For the extension to two players non-stochastic games, there's no more
> randomness. Unobservability is still ok.
> The point is that in non-fully observable games, even when they are
> deterministic, there is a probability c of winning for an optimal stochastic
> strategy S at the worst case on the opponent's stochastic strategies S'.
> This is well defined, and so the question "given graph G (equipped with
> decision nodes for player 1 and decision nodes for player 2), is c bigger
> than d ?" makes sense, and is undecidable.
>
> Importantly, approximate answers are also undecidable.
>
> (nb: my email address is [email protected], [email protected],
> [email protected], all of them leading to the same email account)
>
>
> could you be a bit more precise with your definition of the language you'd
>> like to show is undecidable? try to phrase it as a decision question that
>> results in a language of strings over some finite alphabet, and then maybe
>> you can get somewhere, with a reduction, for instance.
>>
>> i'm not sure how you intend to define undecidability in the face of
>> randomness, or even what your question is really asking.
>>
>> a natural way to use computability to include the flavor of randomness is
>> to bound the number of bad cases. i.e., to imagine that something is
>> happening either uniformly at random or with a particular distribution, and
>> to bound the probability in the uniform case is just to bound the number of
>> bad cases in the deterministic case. but you have to be careful about how
>> you state this.
>>
>> it could be a fairly straightforward undecidability result, but it depends
>> upon the question that you're asking.
>>
>> PS i tried to email you directly instead, but apparently your return email
>> address is invalid...
>>
>> s.
>>
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>>
>
>
>
> --
> =========================================================
> Olivier Teytaud -- [email protected]
> TAO, LRI, UMR 8623(CNRS - Universite Paris-Sud),
> bat 490 Universite Paris-Sud F-91405 Orsay Cedex France http://0z.fr/EJm0g
> (one of the 56.5 % of french who did not vote for Sarkozy in 2007)
>
>
>
>
>
> --
> =========================================================
> Olivier Teytaud -- [email protected]
> TAO, LRI, UMR 8623(CNRS - Universite Paris-Sud),
> bat 490 Universite Paris-Sud F-91405 Orsay Cedex France http://0z.fr/EJm0g
> (one of the 56.5 % of french who did not vote for Sarkozy in 2007)
>
>
>


-- 
=========================================================
Olivier Teytaud -- [email protected]
TAO, LRI, UMR 8623(CNRS - Universite Paris-Sud),
bat 490 Universite Paris-Sud F-91405 Orsay Cedex France http://0z.fr/EJm0g
(one of the 56.5 % of french who did not vote for Sarkozy in 2007)
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