Knowledge Spaces and Learning Spaces

How to design automated procedures which (i) accurately assess the knowledge of a student, and (ii) efficiently provide advices for further study? To produce well-founded answers, Knowledge Space Theory relies on a combinatorial viewpoint on the assessment of knowledge, and thus departs from common, numerical evaluation. Its assessment procedures fundamentally differ from other current ones (such as those of S.A.T. and A.C.T.). They are adaptative (taking into account the possible correctness of previous answers from the student) and they produce an outcome which is far more informative than a crude numerical mark. This chapter recapitulates the main concepts underlying Knowledge Space Theory and its special case, Learning Space Theory. We begin by describing the combinatorial core of the theory, in the form of two basic axioms and the main ensuing results (most of which we give without proofs). In practical applications, learning spaces are huge combinatorial structures which may be difficult to manage. We outline methods providing efficient and comprehensive summaries of such large structures. We then describe the probabilistic part of the theory, especially the Markovian type processes which are instrumental in uncovering the knowledge states of individuals. In the guise of the ALEKS system, which includes a teaching component, these methods have been used by millions of students in schools and colleges, and by home schooled students. We summarize some of the results of these applications

Note: Axiomatic Derivation of the Doppler Factor and Related Relativistic Laws

The formula for the relativistic Doppler effect is investigated in the context of two compelling invariance axioms. The axioms are expressed in terms of an abstract operation generalizing the relativistic addition of velocities. We prove the following results. (1) If the standard representation for the operation is not assumed a priori, then each of the two axioms is consistent with both the relativistic Doppler effect formula and the Lorentz-Fitzgerald Contraction. (2) If the standard representation for the operation is assumed, then the two axioms are equivalent to each other and to the relativistic Doppler effect formula. Thus, the axioms are inconsistent with the Lorentz-FitzGerald Contraction in this case. (3) If the Lorentz-FitzGerald Contraction is assumed, then the two axioms are equivalent to each other and to a different mathematical representation for the operation which applies in the case of perpendicular motions. The relativistic Doppler effect is derived up to one positive exponent parameter (replacing the square root). We prove these facts under regularity and other reasonable background conditions.Comment: 12 page

Primary Facets Of Order Polytopes

Mixture models on order relations play a central role in recent investigations of transitivity in binary choice data. In such a model, the vectors of choice probabilities are the convex combinations of the characteristic vectors of all order relations of a chosen type. The five prominent types of order relations are linear orders, weak orders, semiorders, interval orders and partial orders. For each of them, the problem of finding a complete, workable characterization of the vectors of probabilities is crucial---but it is reputably inaccessible. Under a geometric reformulation, the problem asks for a linear description of a convex polytope whose vertices are known. As for any convex polytope, a shortest linear description comprises one linear inequality per facet. Getting all of the facet-defining inequalities of any of the five order polytopes seems presently out of reach. Here we search for the facet-defining inequalities which we call primary because their coefficients take only the values -1, 0 or 1. We provide a classification of all primary, facet-defining inequalities of three of the five order polytopes. Moreover, we elaborate on the intricacy of the primary facet-defining inequalities of the linear order and the weak order polytopes

Identifiability in Knowledge Space Theory: a survey of recent results

Knowledge Space Theory (KST) links in several ways to Formal Concept Analysis (FCA). Recently, the probabilistic and statistical aspects of KST have been further developed by several authors. We review part of the recent results, and describe some of the open problems. The question of whether the outcomes can be useful in FCA remains to be investigated

Weighted graphs defining facets: a connection between stable set and linear ordering polytopes

A graph is alpha-critical if its stability number increases whenever an edge is removed from its edge set. The class of alpha-critical graphs has several nice structural properties, most of them related to their defect which is the number of vertices minus two times the stability number. In particular, a remarkable result of Lov\'asz (1978) is the finite basis theorem for alpha-critical graphs of a fixed defect. The class of alpha-critical graphs is also of interest for at least two topics of polyhedral studies. First, Chv\'atal (1975) shows that each alpha-critical graph induces a rank inequality which is facet-defining for its stable set polytope. Investigating a weighted generalization, Lipt\'ak and Lov\'asz (2000, 2001) introduce critical facet-graphs (which again produce facet-defining inequalities for their stable set polytopes) and they establish a finite basis theorem. Second, Koppen (1995) describes a construction that delivers from any alpha-critical graph a facet-defining inequality for the linear ordering polytope. Doignon, Fiorini and Joret (2006) handle the weighted case and thus define facet-defining graphs. Here we investigate relationships between the two weighted generalizations of alpha-critical graphs. We show that facet-defining graphs (for the linear ordering polytope) are obtainable from 1-critical facet-graphs (linked with stable set polytopes). We then use this connection to derive various results on facet-defining graphs, the most prominent one being derived from Lipt\'ak and Lov\'asz's finite basis theorem for critical facet-graphs. At the end of the paper we offer an alternative proof of Lov\'asz's finite basis theorem for alpha-critical graphs

Le cône des représentations d’un ordre d’intervalles

Un ordre d’intervalles est donné sur un ensemble fini d’éléments. Définies de manière appropriée, ses représentations numériques forment un polyèdre convexe. Nos résultats décrivent la structure géométrique de ce polyèdre. Les facettes correspondent à des objets de quatre types : les éléments minimaux, les éléments contractibles ainsi que les nez et les creux de l’ordre d’intervalles (ces deux dernières notions sont inspirées de Doignon et Falmagne [1997]). Le polyèdre n’a qu’un seul sommet, qui est la représentation minimale de l’ordre d’intervalles (au sens de Doignon [1988a] ; plusieurs nouvelles propriétés sont établies ici). Les représentations forment donc un cône convexe. Nous caractérisons les rayons extrêmes de ce cône. L’unicité du sommet est un résultat surprenant, car Balof, Doignon et Fiorini [2012] ont obtenu, pour le polyèdre des représentations d’un semiordre, de nombreux exemples à sommets multiplesA fixed, interval order is considered on a finite set of elements. When appropriately defined, its representations form a convex polyhedron. Our results describe the geometricstructure of the polyhedron. The facets are in a one-to-one correspondence with the objects of oneof four types: the minimal elements, the contractible elements as well as the noses and the hollowsof the interval order (the latter notions are inferred from Doignon and Falmagne [1997]). Thepolyhedron has only one vertex, which is the minimal representation (in the meaning of Doignon[1988a]; new properties are established here). All representations thus form a convex cone. Wecharacterize the extreme rays of this cone. The uniqueness of the vertex came as a surprise tous surprise because Balof, Doignon and Fiorini [2012] obtained, for the polyhedron formed by allrepresentations of a semiorder, numerous examples with multiple vertices

The approval-voting polytope: combinatorial interpretation of the facets

Doignon and Fiorini (2003)determine all facets of the approval-voting polytope, thus offering a characterization of the size-independent model for approval voting of Falmagne and Regenwetter (1996). The present paper is a follow-up. It first provides an alternate proof of the basic result, which is more direct and at the same time constructive. Then, the combinatorial interpretation of the facets of the approval-voting polytope is further investigated. Finally, we derive a linear description of the polytope in case the number of alternatives equals 6.Doignon et Fiorini (2003) déterminent toutes les facettes du polytope du vote approbatoire. Ils livrent ainsi une caractérisation d'un modèle probabiliste dû à Falmagne et Regenwetter (1996) : le modèle sous indépendance de taille pour le vote approbatoire. Le présent texte est un complément. Il donne d'abord une preuve alternative du résultat central, plus directe mais aussi constructive. L'interprétation combinatoire des facettes du polytope du vote approbatoire est ensuite étudiée. Enfin, une description linéaire du polytope est obtenue dans le cas où le nombre d'alternatives vaut 6

Minimum Numbers of Circuits in Affine Sets

Motivated by a question due to J. Eckhoff, we look for the minimum of the number of circuits contained in a subset of s points in a d-dimensional affine space, with fixed s and d. © 1981, Academic Press Inc. (London) Limited. All rights reserved.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Segments et ensembles convexes

Doctorat en Sciencesinfo:eu-repo/semantics/nonPublishe