201 research outputs found

    The Difficulties of Learning Logic Programs with Cut

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    As real logic programmers normally use cut (!), an effective learning procedure for logic programs should be able to deal with it. Because the cut predicate has only a procedural meaning, clauses containing cut cannot be learned using an extensional evaluation method, as is done in most learning systems. On the other hand, searching a space of possible programs (instead of a space of independent clauses) is unfeasible. An alternative solution is to generate first a candidate base program which covers the positive examples, and then make it consistent by inserting cut where appropriate. The problem of learning programs with cut has not been investigated before and this seems to be a natural and reasonable approach. We generalize this scheme and investigate the difficulties that arise. Some of the major shortcomings are actually caused, in general, by the need for intensional evaluation. As a conclusion, the analysis of this paper suggests, on precise and technical grounds, that learning cut is difficult, and current induction techniques should probably be restricted to purely declarative logic languages.Comment: See http://www.jair.org/ for any accompanying file

    An interactive system to learn functional logic programs

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    Abstract The problem of learning functional logic programs from positive examples is addressed. We describe a system, called FILP, which asks existential queries to the user, and is able to learn multiple predicates and recursive clauses. We prove that the learned descriptions are correct in the sense that they are consistent with the given examples. Moreover, a correct solution is always found if it exists

    Testing by means of inductive program learning

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    Given a program P and a set of alternative programs //’, we generate a sequence of test cases that are adequate, in the sense that they distinguish the given program from all alternatives The, m(,thod is related to fault-based approaches to test case generation, but programs in P need not he s]mp]e mutations of P. The technique for generating an adequate test set is based on the inductive learning of programs from finite sets of input-output examples: given a partial test set. we generate inductively a program P ’ E P which is consistent with P on those input values; then we look for an input value that distinguishes P from P’, and we repeat the process until no program except P can be induced from the generated examples. We show that the obtained test set is adequate with respect to the alternatives belonging to P. The method IS made possible by a program induction procedure which has evolved from recent research in mnchine Iei]rnlng and inductive logic programming. An implemented version of the test case ~encration procedure is demonstrated on simple and more complex list-processing programs. and tb(, scalability of ’ the approach is discussed

    Abduction in Machine Learning

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    Riuso “caldo” e “freddo” di dispositivi negli archivi di Albe e Lica Steiner e AG Fronzoni attraverso produzioni storiografiche e didattiche. La rivista u e il periodico u

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    Albe Steiner ha lasciato un archivio pronto all’uso, con dispositivi che lavorano sul principio del “sistema delle immagini”, al contrario l’esperienza intellettuale di ricerca visiva di AG Fronzoni ha prodotto dei dispositivi a riuso “freddo” di narrazione dei progetti. Il processo di reperimento, analisi e sintesi delle fonti prodotte dai due progettisti è simile a quello di due etnologi che hanno costruito le proprie culture visive con due prospettive metodologiche: regime autoriale per Steiner e regime classificatorio per Fronzoni. Con modalità e processi differenti entrambi i progettisti uniscono la fenomenologia della loro produzione progettuale al loro pensiero critico: produzione di una storiografia socialmente orientata per i coniugi Steiner e i loro eredi, e mancanza di produzione di pubblicazioni per Fronzoni, ma presenza di una storia orale, originata nella sua didattica e narrata dai suoi allievi. La transizione tra due paradigmi – Atlante di Aby Warburg (1924-29) e Actor Network Theory di Bruno Latour, Michel Callon, e John Law (metà anni ottanta) – consente di esplorare i modi in cui gli archivi mantengono le connessioni e gli scambi significativi fra progettisti e studiosi, in tempi e situazioni culturali diverse, attraverso dispositivi come narrazioni di identità, letteratura critica, archivi e didattica gestite da vecchi e nuovi linguaggi, analogici e digitali. Guardandoli in questa ottica da un lato ci sarebbero archivi “esistenti” o “pronti per l’uso”, dall’altro archivi “in costruzione” che passano dallo stato di “fatto” o di “artefatto” al worknet. La poetica dell’insegnamento di AG Fronzoni è potenziale “esistente” di una storia orale e politica della sua opera e del suo archivio, la politica nella vita di Albe e Lica Steiner e la memoria del loro insegnamento sono il manifestarsi in progress del loro archivio in un progetto culturale condiviso e autorevole. Proponiamo in questo saggio un lavoro di ricerca su due dispositivi-attori, conservati negli archivi dei due progettisti, la rivista U della scuola Umanitaria e il giornale U della municipalità di Urbino. Il primo progetto didattico attraversa l’esperienza intellettuale di AG Fronzoni rimettendo in sequenza un riuso freddo delle immagini, e si confronta con il secondo progetto didattico basato sul riuso caldo del sistema delle immagini di Steiner, in un circuito ermeneutico orientato alla storia orale e a una storiografia sociale del progetto grafico

    An intelligent agent based autonomous mission management system for UAVs.

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    Unmanned Aerial Vehicles (UAVs) have been around for almost eight decades, but they evolved from the basic remotely-controlled form only during the last two. While UAV-related research encompasses several areas, the increase of autonomy is certainly one of the most important topics. Current-generation UAVs are typically able to autonomously execute a pre-planned mission, and there is a definite trend towards increased UAV autonomy. The main challenge related to UAV autonomy is the reaction to unforeseen events; the capability to execute pre-planned tasks does not take into account the fact that in a dynamic environment the plan might need to be changed. This Mission Management activity is usually tasked to human supervision. Within this thesis, the problem of UAV autonomy will be addressed by proposing a software architecture that allows the integration of various technologies to obtain a significant improvement in the autonomy level of UAV. The first step in this is the definition of a set of theoretical concepts that allow the computational description of three different types of information: user-generated mission objectives, knowledge regarding the external environment and complete flight plans. The second step is then to develop a software system that autonomously accomplishes the Mission Management task: combining mission objectives and environmental knowledge to generate a viable flight plan, then update it when situational awareness changes. The software system presented in this thesis is implemented using a combination of three separate Soar Intelligent Agents and traditional control techniques. Soar (State, Operator and Result) is the computational implementation of a general theory of cognition, allowing for the definition of complex software agents which can efficiently apply the rules defining their behaviour to large amounts of knowledge. Soar agents are used to provide high-level reasoning capability to the system, while low-level control functions are better performed by traditional algorithms. The software system is fully described and implemented, then tested in a simulation environment. Simulations are used to demonstrate the system’s ability to automatically generate, execute and update (when necessary) an entire flight plan after being assigned a set of mission objectives
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