Re: perfect knowledge in AI

No, perfection implies logical correctness within the defined constraints
of representation, but under the open-world assumption, it should not imply
completeness.


On Mon, 9 May 2022 at 11:30, Paola Di Maio <paoladimaio10@gmail.com> wrote:

>
> Does Perfection imply completeness?
> Discuss
>
>
> On Mon, May 9, 2022 at 2:47 PM ProjectParadigm-ICT-Program <
> metadataportals@yahoo.com> wrote:
>
>> If perfect implies complete, we can rule it out because of the proofs by
>> Godel and Turing on incompleteness and undecidability.
>> The concept of perfect only exists in mathematics with the definition of
>> perfect numbers.
>> Unbiased reasoning that leads to results for which truth values can be
>> determined in terms of validity, reproducibility, equivalence and causal
>> relationships are the best way to go for knowledge representation.
>> Knowledge and for that matter consciousness as well are as yet not
>> unequivocally defined, and as such perfection in this context is not
>> attainable.
>>
>>
>> Milton Ponson
>> GSM: +297 747 8280
>> PO Box 1154, Oranjestad
>> Aruba, Dutch Caribbean
>> Project Paradigm: Bringing the ICT tools for sustainable development to
>> all stakeholders worldwide through collaborative research on applied
>> mathematics, advanced modeling, software and standards development
>>
>>
>> On Sunday, May 8, 2022, 04:15:01 AM AST, Paola Di Maio <
>> paola.dimaio@gmail.com> wrote:
>>
>>
>> Dave R's latest post  to the cog ai list reminds us of the ultimate.
>> Perfect knowledge is a thing. Is there any such thing, really? How can it
>> be pursued?
>> Can we distinguish
>> perfect knowledge rom its perfect representation
>>
>>
>> Much there is to say about it. In other schools, we start by clearing the
>> obscurations in our own mind  . That is a lifetime pursuit.
>> While we get there, I take the opportunity to reflect on the perfect
>> knowledge literature in AI, a worthy topic to remember
>>
>> I someone would like to access the article below, email me, I can share
>> my copy
>>
>>
>> ARTIFICIAL INTELLIGENCE 111
>> Perfect Knowledge Revisited*
>> S.T. Dekker, H.J. van den Herik and
>> l.S. Herschberg
>> Delft University of Technology, Department of Mathematics
>> and Informatics, 2628 BL Delft, Netherlands
>> ABSTRACT
>> Database research slowly arrives at the stage where perfect knowledge
>> allows us to grasp simple
>> endgames which, in most instances, show pathologies never thought o f by
>> Grandmasters' intuition.
>> For some endgames, the maximin exceeds FIDE's 50-move rule, thus
>> precipitating a discussion
>> about altering the rule. However, even though it is now possible to
>> determine exactly the path lengths
>> o f many 5-men endgames (or o f fewer men), it is felt there is an
>> essential flaw if each endgame
>> should have its own limit to the number o f moves. This paper focuses on
>> the consequences o f a
>> k-move rule which, whatever the value o f k, may change a naive optimal
>> strategy into a k-optimal
>> strategy which may well be radically different.
>> 1. Introduction
>> Full knowledge of some endgames involving 3 or 4 men has first been made
>> available by Str6hlein [12]. However, his work did not immediately
>> receive the
>> recognition it deserved. This resulted in several reinventions of the
>> retrograde
>> enumeration technique around 1975, e.g., by Clarke, Thompson and by
>> Komissarchik and Futer. Berliner [2] reported in the same vein at an
>> early date
>> as did Newborn [11]. It is only recent advances in computers that allowed
>> comfortably tackling endgames of 5 men, though undaunted previous efforts
>> are on record (Komissarchik and Futer [8], Arlazarov and Futer [1]). Over
>> the
>> past four years, Ken Thompson has been a conspicuous labourer in this
>> particular field (Herschberg and van den Herik [6], Thompson [13]).
>> As of this writing, three 3-men endgames, five 4-men endgames, twelve
>> 5-men endgames without pawns and three 5-men endgames with a pawn [4] can
>> be said to have been solved under the convention that White is the
>> stronger
>> *The research reported in this contribution has been made possible by the
>> Netherlands
>> Organization for Advancement of Pure Research (ZWO), dossier number 39 SC
>> 68-129, notably
>> by their donation of computer time on the Amsterdam Cyber 205. The
>> opinions expressed are
>> those of the authors and do not necessarily represent those of the
>> Organization.
>> Artificial Intelligence 43 (1990) 111-123
>> 0004-3702/90/$3.50 © 1990, Elsevier Science Publishers B.V.
>> (North-Holland)
>> 112 S.T. D E K K E R ET AL.
>> side and Black provides optimal resistance, which is to say that Black
>> will delay
>> as long as possible either mate or an inevitable conversion into another
>> lost
>> endgame. Conversion is taken in its larger sense. It may consist in
>> converting
>> to an endgame of different pieces, e.g., by promoting a pawn; equally, it
>> may
>> involve the loss of a piece and, finally and most subtly, it may involve
>> a pawn
>> move which turns an endgame into an essentially different endgame: a case
>> in
>> point is the pawn move in the KQP(a6)KQ endgame converting it into
>> KQP(a7)KQ (for notation, see Appendix A).
>> The database, when constructed, defines an entry for every legal
>> configura-
>> tion; from this, for each position, a sequence of moves known to be
>> optimal
>> can be derived. The retrograde analysis is performed by a full-width
>> backward-
>> chaining procedure, starting from definitive positions (mate or
>> conversion), as
>> described in detail by van den Herik and Herschberg [18]; this yields a
>> database. The maximum length of all optimal paths is called the maximin
>> (von
>> Neumann and Morgenstern [16]), i.e., the number of moves necessary and
>> sufficient to reach a definitive position from an arbitrary given
>> position with
>> White to move (WTM) and assuming optimal defence
>> CONCLUSION
>> It has now become clear that the notion of optimal play has been rather
>> naively
>> defined so far. At the very least, the notion of optimality requires a
>> specific
>> value of k for k-optimality and hence a careful bookkeeping of all
>> relevant
>> anteriorities. These additional requirements form but one instance of
>> aiming to
>> achieve optimal play under constraints; of such constraints a k-move rule
>> is
>> merely one instance. In essence, it is not our opinion that a k-move rule
>> spoils
>> the game of chess; on the contrary, like any other constraint, it may be
>> said to
>> enrich it, even though at present it appears to puzzle database
>> constructors,
>> chess theoreticians and Grandmasters alike.
>>
>>
>>