Knowledge Representation for Learning How to Evaluate Partial Plans

Slawomir Nowaczyk

    Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKonferenspaper i proceedingPeer review

    29 Nedladdningar (Pure)

    Sammanfattning

    In this paper we present some ideas for knowledge representation formalism suitable for rational agents which learn how to choose the best conditional, partial plan in any given situation. In our architecture, the agent uses an incomplete symbolic inference engine, employing Active Logic, to reason about consequences of performing actions — including information-providing ones. It utilises a simple planner to create conditional partial plans, i.e. ones which do not necessarily
    lead all the way to the ultimate goal. Finally, a learning
    module — based on ILP mechanisms — provides, from experience, knowledge on how to choose which of those plans ought to be executed.
    We discuss principles which should guide design of knowledge representations in order to best fit the requirements of learning process. Clearly, simply presenting all of agent’s knowledge to the ILP algorithm is very inefficient. On the other hand, for many particular applications some very effective
    representations are known. We compare several approaches,
    analysing the tradeoff between amount of domain
    specific knowledge provided and the quality of solutions obtained.
    In the experiments presented we used PROGOL for learning,
    and one of the conclusions of this paper is that some
    algorithm better suited for the particular problem of evaluating plans could significantly improve the competitiveness of domain-independent solutions.
    Originalspråkengelska
    Titel på värdpublikationProceedings of the 24th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS-07)
    StatusPublished - 2007
    EvenemangThe 24th Annual Workshop of the Swedish Artificial Intelligence Society, SAIS 2007 - Borås, Sverige
    Varaktighet: 2007 maj 222007 maj 23

    Publikationsserier

    Namn
    ISSN (tryckt)0348-0542

    Konferens

    KonferensThe 24th Annual Workshop of the Swedish Artificial Intelligence Society, SAIS 2007
    Land/TerritoriumSverige
    OrtBorås
    Period2007/05/222007/05/23

    Ämnesklassifikation (UKÄ)

    • Datavetenskap (datalogi)

    Fingeravtryck

    Utforska forskningsämnen för ”Knowledge Representation for Learning How to Evaluate Partial Plans”. Tillsammans bildar de ett unikt fingeravtryck.

    Citera det här