4,097 research outputs found

### A Map of Update Constraints in Inductive Inference

We investigate how different learning restrictions reduce learning power and
how the different restrictions relate to one another. We give a complete map
for nine different restrictions both for the cases of complete information
learning and set-driven learning. This completes the picture for these
well-studied \emph{delayable} learning restrictions. A further insight is
gained by different characterizations of \emph{conservative} learning in terms
of variants of \emph{cautious} learning.
Our analyses greatly benefit from general theorems we give, for example
showing that learners with exclusively delayable restrictions can always be
assumed total.Comment: fixed a mistake in Theorem 21, result is the sam

### Combining Models of Approximation with Partial Learning

In Gold's framework of inductive inference, the model of partial learning
requires the learner to output exactly one correct index for the target object
and only the target object infinitely often. Since infinitely many of the
learner's hypotheses may be incorrect, it is not obvious whether a partial
learner can be modifed to "approximate" the target object.
Fulk and Jain (Approximate inference and scientific method. Information and
Computation 114(2):179--191, 1994) introduced a model of approximate learning
of recursive functions. The present work extends their research and solves an
open problem of Fulk and Jain by showing that there is a learner which
approximates and partially identifies every recursive function by outputting a
sequence of hypotheses which, in addition, are also almost all finite variants
of the target function.
The subsequent study is dedicated to the question how these findings
generalise to the learning of r.e. languages from positive data. Here three
variants of approximate learning will be introduced and investigated with
respect to the question whether they can be combined with partial learning.
Following the line of Fulk and Jain's research, further investigations provide
conditions under which partial language learners can eventually output only
finite variants of the target language. The combinabilities of other partial
learning criteria will also be briefly studied.Comment: 28 page

### A Description Logic of Typicality for Conceptual Combination

We propose a nonmonotonic Description Logic of typicality able to
account for the phenomenon of combining prototypical concepts, an open problem
in the fields of AI and cognitive modelling. Our logic extends the logic of
typicality ALC + TR, based on the notion of rational closure, by inclusions
p :: T(C) v D (“we have probability p that typical Cs are Ds”), coming
from the distributed semantics of probabilistic Description Logics. Additionally,
it embeds a set of cognitive heuristics for concept combination. We show that the
complexity of reasoning in our logic is EXPTIME-complete as in ALC

### Experimental Evidence for Quantum Structure in Cognition

We proof a theorem that shows that a collection of experimental data of
membership weights of items with respect to a pair of concepts and its
conjunction cannot be modeled within a classical measure theoretic weight
structure in case the experimental data contain the effect called
overextension. Since the effect of overextension, analogue to the well-known
guppy effect for concept combinations, is abundant in all experiments testing
weights of items with respect to pairs of concepts and their conjunctions, our
theorem constitutes a no-go theorem for classical measure structure for common
data of membership weights of items with respect to concepts and their
combinations. We put forward a simple geometric criterion that reveals the non
classicality of the membership weight structure and use experimentally measured
membership weights estimated by subjects in experiments to illustrate our
geometrical criterion. The violation of the classical weight structure is
similar to the violation of the well-known Bell inequalities studied in quantum
mechanics, and hence suggests that the quantum formalism and hence the modeling
by quantum membership weights can accomplish what classical membership weights
cannot do.Comment: 12 pages, 3 figure

### Classical Logical versus Quantum Conceptual Thought: Examples in Economics, Decision theory and Concept Theory

Inspired by a quantum mechanical formalism to model concepts and their
disjunctions and conjunctions, we put forward in this paper a specific
hypothesis. Namely that within human thought two superposed layers can be
distinguished: (i) a layer given form by an underlying classical deterministic
process, incorporating essentially logical thought and its indeterministic
version modeled by classical probability theory; (ii) a layer given form under
influence of the totality of the surrounding conceptual landscape, where the
different concepts figure as individual entities rather than (logical)
combinations of others, with measurable quantities such as 'typicality',
'membership', 'representativeness', 'similarity', 'applicability', 'preference'
or 'utility' carrying the influences. We call the process in this second layer
'quantum conceptual thought', which is indeterministic in essence, and contains
holistic aspects, but is equally well, although very differently, organized
than logical thought. A substantial part of the 'quantum conceptual thought
process' can be modeled by quantum mechanical probabilistic and mathematical
structures. We consider examples of three specific domains of research where
the effects of the presence of quantum conceptual thought and its deviations
from classical logical thought have been noticed and studied, i.e. economics,
decision theory, and concept theories and which provide experimental evidence
for our hypothesis.Comment: 14 page

### Meaning-focused and Quantum-inspired Information Retrieval

In recent years, quantum-based methods have promisingly integrated the
traditional procedures in information retrieval (IR) and natural language
processing (NLP). Inspired by our research on the identification and
application of quantum structures in cognition, more specifically our work on
the representation of concepts and their combinations, we put forward a
'quantum meaning based' framework for structured query retrieval in text
corpora and standardized testing corpora. This scheme for IR rests on
considering as basic notions, (i) 'entities of meaning', e.g., concepts and
their combinations and (ii) traces of such entities of meaning, which is how
documents are considered in this approach. The meaning content of these
'entities of meaning' is reconstructed by solving an 'inverse problem' in the
quantum formalism, consisting of reconstructing the full states of the entities
of meaning from their collapsed states identified as traces in relevant
documents. The advantages with respect to traditional approaches, such as
Latent Semantic Analysis (LSA), are discussed by means of concrete examples.Comment: 11 page

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### Effects of classification context on categorization in natural categories

The patterns of classification of borderline instances of eight common taxonomic categories were examined under three different instructional conditions to test two predictions: first, that lack of a specified context contributes to vagueness in categorization, and second, that altering the purpose of classification can lead to greater or lesser dependence on similarity in classification. The instructional conditions contrasted purely pragmatic with more technical/quasi-legal contexts as purposes for classification, and these were compared with a no-context control. The measures of category vagueness were between-subjects disagreement and within-subjects consistency, and the measures of similarity based categorization were category breadth and the correlation of instance categorization probability with mean rated typicality, independently measured in a neutral context. Contrary to predictions, none of the measures of vagueness, reliability, category breadth, or correlation with typicality were generally affected by the instructional setting as a function of pragmatic versus technical purposes. Only one subcondition, in which a situational context was implied in addition to a purposive context, produced a significant change in categorization. Further experiments demonstrated that the effect of context was not increased when participants talked their way through the task, and that a technical context did not elicit more all-or-none categorization than did a pragmatic context. These findings place an important boundary condition on the effects of instructional context on conceptual categorization

### PRORAČUN ČELIČNIH TANKOSTIJENIH NOSAČA PREMA EN 1993-1-3

Osnovni problem čeličnih tankostijenih nosača, lokalni instabilitet dijelova poprečnog presjeka koji se nalaze u tlaku, može se riješiti povoljnim profiliranjem (ukrućivanjem) poprečnog presjeka nosača. Optimizacijom rasporeda ukrućenja u poprečnom presjeku može se u potpunosti spriječiti lokalni instabilitet te time povećati otpornost nosača bez dodatnog utroška materijala.Veliki utjecaj na otpornost ovakvih nosača, osim ukrućenja, može imati i pridržanje pojasnice profiliranim limom. U članku su prikazani normirani postupci kojima se na brz i jednostavan način može proračunati utjecaj ukrućenja i utjecaj pridržanja pojasnice nosača pokrovnim limom. Konkretnim primjerom kvantificiran je utjecaj ukrućenja i pridržanja pojasnice C podrožnice trapeznim limom. Naglašene su mogućnosti suvremene norme EN 1993-1-3, koje uz malo dodatnog projektantskog napora na jednostavan način omogućuju znatnu uštedu koja se može polučiti iz realnog razmatranja tankostijenih profila

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