31,404 research outputs found
Plan-based delivery composition in intelligent tutoring systems for introductory computer programming
In a shell system for the generation of intelligent tutoring systems, the instructional model that one applies should be variable independent of the content of instruction. In this article, a taxonomy of content elements is presented in order to define a relatively content-independent instructional planner for introductory programming ITS's; the taxonomy is based on the concepts of programming goals and programming plans. Deliveries may be composed by the instantiation of delivery templates with the content elements. Examples from two different instructional models illustrate the flexibility of this approach. All content in the examples is taken from a course in COMAL-80 turtle graphics
On graph equivalences preserved under extensions
Let R be an equivalence relation on graphs. By the strengthening of R we mean
the relation R' such that graphs G and H are in the relation R' if for every
graph F, the union of the graphs G and F is in the relation R with the union of
the graphs H and F. We study strengthenings of equivalence relations on graphs.
The most important case that we consider concerns equivalence relations defined
by graph properties. We obtain results on the strengthening of equivalence
relations determined by the properties such as being a k-connected graph,
k-colorable, hamiltonian and planar
Least Generalizations and Greatest Specializations of Sets of Clauses
The main operations in Inductive Logic Programming (ILP) are generalization
and specialization, which only make sense in a generality order. In ILP, the
three most important generality orders are subsumption, implication and
implication relative to background knowledge. The two languages used most often
are languages of clauses and languages of only Horn clauses. This gives a total
of six different ordered languages. In this paper, we give a systematic
treatment of the existence or non-existence of least generalizations and
greatest specializations of finite sets of clauses in each of these six ordered
sets. We survey results already obtained by others and also contribute some
answers of our own. Our main new results are, firstly, the existence of a
computable least generalization under implication of every finite set of
clauses containing at least one non-tautologous function-free clause (among
other, not necessarily function-free clauses). Secondly, we show that such a
least generalization need not exist under relative implication, not even if
both the set that is to be generalized and the background knowledge are
function-free. Thirdly, we give a complete discussion of existence and
non-existence of greatest specializations in each of the six ordered languages.Comment: See http://www.jair.org/ for any accompanying file
On the Expressive Power of Multiple Heads in CHR
Constraint Handling Rules (CHR) is a committed-choice declarative language
which has been originally designed for writing constraint solvers and which is
nowadays a general purpose language. CHR programs consist of multi-headed
guarded rules which allow to rewrite constraints into simpler ones until a
solved form is reached. Many empirical evidences suggest that multiple heads
augment the expressive power of the language, however no formal result in this
direction has been proved, so far.
In the first part of this paper we analyze the Turing completeness of CHR
with respect to the underneath constraint theory. We prove that if the
constraint theory is powerful enough then restricting to single head rules does
not affect the Turing completeness of the language. On the other hand,
differently from the case of the multi-headed language, the single head CHR
language is not Turing powerful when the underlying signature (for the
constraint theory) does not contain function symbols.
In the second part we prove that, no matter which constraint theory is
considered, under some reasonable assumptions it is not possible to encode the
CHR language (with multi-headed rules) into a single headed language while
preserving the semantics of the programs. We also show that, under some
stronger assumptions, considering an increasing number of atoms in the head of
a rule augments the expressive power of the language.
These results provide a formal proof for the claim that multiple heads
augment the expressive power of the CHR language.Comment: v.6 Minor changes, new formulation of definitions, changed some
details in the proof
Strong Equivalence of Qualitative Optimization Problems
We introduce the framework of qualitative optimization problems (or, simply, optimization problems) to represent preference theories. The formalism uses separate modules to describe the space of outcomes to be compared (the generator) and the preferences on outcomes (the selector). We consider two types of optimization problems. They differ in the way the generator, which we model by a propositional theory, is interpreted: by the standard propositional logic semantics, and by the equilibrium-model (answer-set) semantics. Under the latter interpretation of generators, optimization problems directly generalize answer-set optimization programs proposed previously. We study strong equivalence of optimization problems, which guarantees their interchangeability within any larger context. We characterize several versions of strong equivalence obtained by restricting the class of optimization problems that can be used as extensions and establish the complexity of associated reasoning tasks. Understanding strong equivalence is essential for modular representation of optimization problems and rewriting techniques to simplify them without changing their inherent properties
Loop Formulas for Description Logic Programs
Description Logic Programs (dl-programs) proposed by Eiter et al. constitute
an elegant yet powerful formalism for the integration of answer set programming
with description logics, for the Semantic Web. In this paper, we generalize the
notions of completion and loop formulas of logic programs to description logic
programs and show that the answer sets of a dl-program can be precisely
captured by the models of its completion and loop formulas. Furthermore, we
propose a new, alternative semantics for dl-programs, called the {\em canonical
answer set semantics}, which is defined by the models of completion that
satisfy what are called canonical loop formulas. A desirable property of
canonical answer sets is that they are free of circular justifications. Some
properties of canonical answer sets are also explored.Comment: 29 pages, 1 figures (in pdf), a short version appeared in ICLP'1
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