620 research outputs found
A Compositional Framework for Preference-Aware Agents
A formal description of a Cyber-Physical system should include a rigorous
specification of the computational and physical components involved, as well as
their interaction. Such a description, thus, lends itself to a compositional
model where every module in the model specifies the behavior of a
(computational or physical) component or the interaction between different
components. We propose a framework based on Soft Constraint Automata that
facilitates the component-wise description of such systems and includes the
tools necessary to compose subsystems in a meaningful way, to yield a
description of the entire system. Most importantly, Soft Constraint Automata
allow the description and composition of components' preferences as well as
environmental constraints in a uniform fashion. We illustrate the utility of
our framework using a detailed description of a patrolling robot, while
highlighting methods of composition as well as possible techniques to employ
them.Comment: In Proceedings V2CPS-16, arXiv:1612.0402
Soft constraint abstraction based on semiring homomorphism
The semiring-based constraint satisfaction problems (semiring CSPs), proposed
by Bistarelli, Montanari and Rossi \cite{BMR97}, is a very general framework of
soft constraints. In this paper we propose an abstraction scheme for soft
constraints that uses semiring homomorphism. To find optimal solutions of the
concrete problem, the idea is, first working in the abstract problem and
finding its optimal solutions, then using them to solve the concrete problem.
In particular, we show that a mapping preserves optimal solutions if and only
if it is an order-reflecting semiring homomorphism. Moreover, for a semiring
homomorphism and a problem over , if is optimal in
, then there is an optimal solution of such that
has the same value as in .Comment: 18 pages, 1 figur
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