Jasper Taylor, Jean Carletta and Chris Mellish
Requirements for Belief Models in Cooperative Dialogue
Models of rationality typically rely on underlying logics that allow
simulated agents to entertain beliefs about one another to any depth
of nesting. We argue that representations of individual deeply
nested beliefs are in principle unnecessary for any cooperative
dialogue. We examine some existing dialogue systems and conclude
that where deeply-nested beliefs are supported, they are used only
in situations where cooperation is not assumed.
Use of deeply-nested beliefs is associated with nested reasoning
(i.e., reasoning about other agents' reasoning), which is limited by
the architecture in most systems. Such systems cope well with
cooperative dialogues because these do not require such reasoning.
We show that summarizing representations of beliefs by conjoining
all levels of nesting beyond the second allows agents capable of
simple planning and plan recognition to cooperate in situations
where agents equipped with unrestricted belief models would need to
embody unrealistic assumptions.
(March 1995; 41 pages)
Ref. No. HCRC/RP-66 Price: UKL 1.60
Massimo Poesio
Semantic Ambiguity and Perceived Ambiguity
I explore some of the issues that arise when trying to establish a connection
between the underspecification hypothesis pursued in the NLP literature and
work on ambiguity in semantics and in the psychological literature. A theory
of underspecification is developed `from the first principles', i.e., starting
from a definition of what it means for a sentence to be semantically ambiguous
and from what we know about the way humans deal with ambiguity. An
underspecified language is specified as the translation language of a grammar
covering sentences that display three classes of semantic ambiguity: lexical
ambiguity, scopal ambiguity, and referential ambiguity. The expressions of this
language denote sets of senses. A formalization of defeasible reasoning with
underspecified representations is presented, based on Default Logic. Some
issues to be confronted by such a formalization are discussed.
(May 1995; 45 pages)
Ref. No. HCRC/RP-68 Price: UKL 1.60
Andrei Mikheev
Domain Knowledge for Natural Language Processing
In this paper we describe the organization and contents of the
knowledge base (KB) developed for the processing of patient discharge
summaries (PDSs)---letters sent by a hospital consultant to a
patient's own doctor. This KB is the major component in the
processing of natural language by our system and includes both the
conceptual and lexical knowledge represented in a uniform way.
Conceptual knowledge in the KB is built and organized in a top-down
fashion and explicitly targeted to represent information which was
identified by domain experts to be important. Linguistic knowledge is
built around the conceptual structures in a bottom-up and empirically
driven way and encode the actual textual representations of particular
classes of conceptual structures. The fundamental idea behind this
approach is grouping of lexical knowledge around conceptual structures
by means of lexico-semantic constructions (LSCs), which cover entire
classes of NL expressions and are prepacked with rules for
deterministic interpretation of these expressions into conceptual
schemata of the domain. Although this KB is explicitly targeted to
the medical domain and its sublanguage we argue that the approach
advocated in this paper can be applied to general i.e. multi-domain
NLP. This requires the parallel development of lexico-semantic
constructions for capturing information from the text and conceptual
structures to accommodate this information. In support of this claim
we present strategies and tools for semi-automatic knowledge
acquisition from the underlying corpus. On the basis of some example
texts and system output, we will illustrate how acquired and
represented background knowledge is used in processing to yield the
desired interpretations.
(July 1995; 31 pages)
Ref. No. HCRC/RP-70 Price: UKL 1.30
Keith Stenning and Richard Tobin
Assigning information to modalities: comparing graphical treatments of
the syllogism
Our long term goal is a cognitive theory of the effects of assigning
information to different media and modalities. Our theory is based on
the observation that graphical representations are limited in their
logical expressiveness and that this leads to tractable inference. Our theory
predicts that usability should be a function of logical expressiveness.
We begin by clarifying the intended senses of media and modalities. We
then suggest a method for studying the cognitive effects of modality
assignment. Comparing alternative assignments of the same information to
different modalities allows many unknown factors affecting usability to be
minimised. We choose categorial syllogisms as an example domain and describe
three methods of varying expressive power for implementing
syllogistic reasoning.
The expressive power of the three systems is then considered and
predictions of usability made. Although empirical evidence about the
usability of the three systems is at present limited, their analysis is
sufficient to raise issues about what is required to connect empirical
observations to the kind of theory sketched here. Strong intuitions
about relative usability of these well-specified systems suggests that
the theory may be developing along promising lines. The intuitively
most usable system is the one whose expressive power is closely matched
to the abstractive requirements of the inferential task at hand.
(September 1995; 23 pages)
Ref. No. HCRC/RP-71 Price: UKL 1.10
Jonathan Ginzburg, Zurab Khasidashvili and Enric Vallduvi, organizers
Tbilisi Symposium on Language, Logic, and Computation
The Tbilisi Symposium on Language, Logic, and Computation, the first of
a regular series, is scheduled to take place in the Republic of Georgia
on October 19-22, 1995. It will be a four-day conference with seven
keynote speakers. 51 papers were submitted (length ca. 10 pages) from
which 26 were selected for presentation. A selection of papers presented
in the conference will be published by CSLI, Stanford.
Contributed papers cover topics such as natural language syntax, formal
semantics, dynamic logic, quantified extensions of modal systems and
intermediate logics, statistics and language processing, automated
deduction and logic programming, process algebras, and lambda and
combinatory calculi. Since work in the fields of Logic, Language and
Computation is currently at a stage where cross--fertilisation is of
increasing importance, it is expected that the proceedings will be of
interest to a wide audience from among researchers in computer science,
artificial intelligence, logic, linguistics and philosophy. In addition,
the proceedings will provide an opportunity for high quality research
from Georgia, Armenia and other FSU countries to reach the international
LLC community.
(September 1995; 67 pages)
Ref. No. HCRC/RP-72 Price: UKL 2.40
Antonio Moreno
Dynamic Belief Analysis
The process of {\em rational inquiry} can be defined as the evolution
of the beliefs of a rational agent as a consequence of its internal
inference procedures or its interaction with the environment. These
beliefs can be modelled in a formal way using {\em doxastic
logics}. The {\em (possible worlds model} and its associated {\em
Kripkean semantics} provide an intuitive semantics for these logics,
but they seem to model agents which are {\em logically omniscient}
(and {\em perfect reasoners.} These problems can be avoided with a
syntactic view of possible worlds, defining them as arbitrary sets of
sentences in a propositional doxastic logic. This approach does not
account for any kind of evolution in the set of beliefs, though. In
this work this syntactic view of possible worlds is taken, and a
three-dimensional dynamic analysis of the beliefs of the agent is
suggested in order to model the process of {\em rational inquiry} in
which the agent is permanently engaged. The agent can make a {\em
logical} analysis of the beliefs (using a modified version of the{\em
analytic tableaux} method); the results of this analysis guide the
{\em experimental} analysis, that allows the agent to perform certain
tests in the environment, that corroborate or refute the results of
the logical analysis. In a third ({\em axiomatic}) kind of analysis,
the agent can transform its set of beliefs into an axiomatic system (a
set of axioms and a set of inference rules.)
(September 1995; 29 pages)
Ref. No. HCRC/RP-73 Price: UKL 1.20