19,928 research outputs found
Adaptation is a Game
Control data variants of game models such as Interface Automata are suitable for the design and analysis of self-adaptive systems
A Case Study on Formal Verification of Self-Adaptive Behaviors in a Decentralized System
Self-adaptation is a promising approach to manage the complexity of modern
software systems. A self-adaptive system is able to adapt autonomously to
internal dynamics and changing conditions in the environment to achieve
particular quality goals. Our particular interest is in decentralized
self-adaptive systems, in which central control of adaptation is not an option.
One important challenge in self-adaptive systems, in particular those with
decentralized control of adaptation, is to provide guarantees about the
intended runtime qualities. In this paper, we present a case study in which we
use model checking to verify behavioral properties of a decentralized
self-adaptive system. Concretely, we contribute with a formalized architecture
model of a decentralized traffic monitoring system and prove a number of
self-adaptation properties for flexibility and robustness. To model the main
processes in the system we use timed automata, and for the specification of the
required properties we use timed computation tree logic. We use the Uppaal tool
to specify the system and verify the flexibility and robustness properties.Comment: In Proceedings FOCLASA 2012, arXiv:1208.432
Adaptation is a game
Control data variants of game models such as Interface Automata are suitable for the design and analysis of self-adaptive systems
Adaptable transition systems
We present an essential model of adaptable transition systems inspired by white-box approaches to adaptation and based on foundational models of component based systems. The key feature of adaptable transition systems are control propositions, imposing a clear separation between ordinary, functional behaviours and adaptive ones. We instantiate our approach on interface automata yielding adaptable interface automata, but it may be instantiated on other foundational models of component-based systems as well. We discuss how control propositions can be exploited in the specification and analysis of adaptive systems, focusing on various notions proposed in the literature, like adaptability, control loops, and control synthesis
Shift operators and complex systems
International audienceIn this paper, we deal with some multiagent systems modelling, based on population of automata.We focus our attention with automatic computation of emerging systems. A multiscale representation is proposed here and consists in representing the internal states of an agent behaviour by a automaton with multiplicities, on the one hand and an adaptive global system behaviour by a genetic algorithm over a population of automata, on the other hand. This genetic process can lead to generate many new automata which behaviour can be eventually similar. The role played by shift operators is to identify these similar behaviours. Two applications are presented. The first one concerns adaptive strategies in game theory. The second one concerns an automatic emerging computation of self-organised multiagent systems based on the efficience of operation expressivity of automata with multiplicities
Automata-based Adaptive Behavior for Economical Modelling Using Game Theory
In this chapter, we deal with some specific domains of applications to game
theory. This is one of the major class of models in the new approaches of
modelling in the economic domain. For that, we use genetic automata which allow
to build adaptive strategies for the players. We explain how the automata-based
formalism proposed - matrix representation of automata with multiplicities -
allows to define semi-distance between the strategy behaviors. With that tools,
we are able to generate an automatic processus to compute emergent systems of
entities whose behaviors are represented by these genetic automata
Automata-based adaptive behavior for economic modeling using game theory
In this paper, we deal with some specific domains of applications to game
theory. This is one of the major class of models in the new approaches of
modelling in the economic domain. For that, we use genetic automata which allow
to buid adaptive strategies for the players. We explain how the automata-based
formalism proposed - matrix representation of automata with multiplicities -
allows to define a semi-distance between the strategy behaviors. With that
tools, we are able to generate an automatic processus to compute emergent
systems of entities whose behaviors are represented by these genetic automata
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