110 research outputs found
Semantics of fuzzy quantifiers
The aim of this thesis is to discuss the semantics of FQs (fuzzy quantifiers),
formal semantics in particular. The approach used is fuzzy semantic based
on fuzzy set theory (Zadeh 1965, 1975), i.e. we explore primarily the denotational
meaning of FQs represented by membership functions. Some empirical
data from both Chinese and English is used for illustration.
A distinguishing characteristic of the semantics of FQs like about 200 students and many students as opposed to other sorts of quantifiers like every
student and no students, is that they have fuzzy meaning boundaries. There
is considerable evidence to suggest that the doctrine that a proposition is either true or false has a limited application in natural languages, which raises
a serious question towards any linguistic theories that are based on a binary
assumption. In other words, the number of elements in a domain that must
satisfy a predicate is not precisety given by an FQ and so a proposition con¬
taining one may be more or less true depending on how closely numbers of
elements approximate to a given norm.
The most significant conclusion drawn here is that FQs are compositional in
that FQs of the same type function in the same way to generate a constant
semantic pattern. It is argued that although basic membership functions are
subject to modification depending on context, they vary only with certain
limits (i.e. FQs are motivated—neither completely predicated nor completely
arbitrary), which does not deny compositionality in any way. A distinctive
combination of compositionality and motivation of FQs makes my formal
semantic framework of FQs unique in the way that although some specific
values, such as a norm, have to be determined pragmatically, semantic and
inferential patterns are systematic and predictable.
A number of interdisciplinary implications, such as semantic, general linguistic, logic and psychological, are discussed. The study here seems to be
a somewhat troublesome but potentially important area for developing theories (and machines) capable of dealing with, and accounting for, natural
languages
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Heuristics, Concepts, and Cognitive Architecture: Toward Understanding How The Mind Works
Heuristics are often invoked in the philosophical, psychological, and cognitive science literatures to describe or explain methodological techniques or shortcut mental operations that help in inference, decision-making, and problem-solving. Yet there has been surprisingly little philosophical work done on the nature of heuristics and heuristic reasoning, and a close inspection of the way(s) in which heuristic is used throughout the literature reveals a vagueness and uncertainty with respect to what heuristics are and their role in cognition. This dissertation seeks to remedy this situation by motivating philosophical inquiry into heuristics and heuristic reasoning, and then advancing a theory of how heuristics operate in cognition. I develop a positive working characterization of heuristics that is coherent and robust enough to account for a broad range of phenomena in reasoning and inference, and makes sense of empirical data in a systematic way. I then illustrate the work this characterization does by considering the sorts of problems that many philosophers believe heuristics solve, namely those resulting from the so-called frame problem. Considering the frame problem motivates the need to gain a better understanding of how heuristics work and the cognitive structures over which they operate. I develop a general theory of cognition which I argue underwrites the heuristic operations that concern this dissertation. I argue that heuristics operate over highly organized systems of knowledge, and I offer a cognitive architecture to accommodate this view. I then provide an account of the systems of knowledge that heuristics are supposed to operate over, in which I suggest that such systems of knowledge are concepts. The upshot, then, is that heuristics operate over concepts. I argue, however, that heuristics do not operate over conceptual content, but over metainformational relations between activated and primed concepts and their contents. Finally, to show that my thesis is empirically adequate, I consider empirical evidence on heuristic reasoning and argue that my account of heuristics explains the data
Proceedings of the IJCAI-09 Workshop on Nonmonotonic Reasoning, Action and Change
Copyright in each article is held by the authors.
Please contact the authors directly for permission to reprint or use this material in any form for any purpose.The biennial workshop on Nonmonotonic Reasoning, Action
and Change (NRAC) has an active and loyal community.
Since its inception in 1995, the workshop has been held seven
times in conjunction with IJCAI, and has experienced growing
success. We hope to build on this success again this eighth
year with an interesting and fruitful day of discussion.
The areas of reasoning about action, non-monotonic reasoning
and belief revision are among the most active research
areas in Knowledge Representation, with rich inter-connections
and practical applications including robotics, agentsystems,
commonsense reasoning and the semantic web.
This workshop provides a unique opportunity for researchers
from all three fields to be brought together at a single forum
with the prime objectives of communicating important recent
advances in each field and the exchange of ideas. As these
fundamental areas mature it is vital that researchers maintain
a dialog through which they can cooperatively explore
common links. The goal of this workshop is to work against
the natural tendency of such rapidly advancing fields to drift
apart into isolated islands of specialization.
This year, we have accepted ten papers authored by a diverse
international community. Each paper has been subject
to careful peer review on the basis of innovation, significance
and relevance to NRAC. The high quality selection of work
could not have been achieved without the invaluable help of
the international Program Committee.
A highlight of the workshop will be our invited speaker
Professor Hector Geffner from ICREA and UPF in Barcelona,
Spain, discussing representation and inference in modern
planning. Hector Geffner is a world leader in planning,
reasoning, and knowledge representation; in addition to his
many important publications, he is a Fellow of the AAAI, an
associate editor of the Journal of Artificial Intelligence Research
and won an ACM Distinguished Dissertation Award
in 1990
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