138 research outputs found
Proving Finite Satisfiability of Deductive Databases
It is shown how certain refutation methods can be extended into semi-decision
procedures that are complete for both unsatisfiability and finite satisfiability. The proposed extension
is justified by a new characterization of finite satisfiability. This research was motivated
by a database design problem: Deduction rules and integrity constraints in definite databases
have to be finitely satisfiabl
Quantified Constraints in Twenty Seventeen
I present a survey of recent advances in the algorithmic and computational complexity theory of non-Boolean Quantified Constraint Satisfaction Problems, incorporating some more modern research directions
Reflective mobile middleware for context-aware applications
The increasing popularity of mobile devices, such as mobile phones and personal digital
assistants, and advances in wireless networking technologies, are enabling new classes
of applications that present challenging problems to application designers. Applications
have to be aware of, and adapt to, variations in the execution context, such as
fluctuating
network bandwidth and decreasing battery power, in order to deliver a good quality of
service to their users.
We argue that building applications directly on top of the network operating system
would be extremely tedious and error-prone, as application developers would have to
deal with these issues explicitly, and would consequently be distracted from the actual
requirements of the application they are building. Rather, a middleware layered between
the network operating system and the application should provide application developers
with abstractions and mechanisms to deal with them.
We investigate the principle of reflection and demonstrate how it can be used to support
context-awareness and dynamic adaptation to context changes. We offer application engineers
an abstraction of middleware as a dynamically customisable service provider, where
each service can be delivered using different policies when requested in different contexts.
Based on this abstraction, current middleware behaviour, with respect to a particular
application, is reified in an application profile, and made accessible to the application for
run-time inspection and adaptation. Applications can use the meta-interface that the
middleware provides to change the information encoded in their profile, thus tailoring
middleware behaviour to the user's needs. However, while doing so, conflicts may arise;
different users may have different quality-of-service needs, and applications, in an attempt
to full these needs, may customise middleware behaviour in conflicting ways. These conflicts have to be resolved in order to allow applications to come to an agreement, and thus
be able to engage successful collaborations.
We demonstrate how microeconomic techniques can be used to treat these kinds of conflicts. We offer an abstraction of the mobile setting as an economy, where applications
compete to have a service delivered according to their quality-of-service needs. We have
designed a mechanism where middleware plays the role of the auctioneer, collecting bids
from the applications and delivering the service using the policy that maximises social
welfare; that is, the one that delivers, on average, the best quality-of-service.
We formalise the principles discussed above, namely reflection to support context-awareness
and microeconomic techniques to support conflict resolution. To demonstrate their effectiveness
in fostering the development of context-aware applications, we discuss a middleware
architecture and implementation (CARISMA) that embed these principles, and report
on performance and usability results obtained during a thorough evaluation stage
Approximate Assertional Reasoning Over Expressive Ontologies
In this thesis, approximate reasoning methods for scalable assertional reasoning are provided whose computational properties can be established in a well-understood way, namely in terms of soundness and completeness, and whose quality can be analyzed in terms of statistical measurements, namely recall and precision. The basic idea of these approximate reasoning methods is to speed up reasoning by trading off the quality of reasoning results against increased speed
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