Adaptive and context-aware reconciliation of reactive and pro-active behavior in evolving systems

Goce Trajcevski*, Peter Scheuermann

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

One distinct characteristics of the context-aware systems is their ability to react and adapt to the evolution of the environment, which is often a result of changes in the values of various (possibly correlated) attributes. Based on these changes, reactive systems typically take corrective actions, e.g., adjusting parameters in order to maintain the desired specifications of the system's state. Pro-active systems, on the other hand, may change the mode of interaction with the environment as well as the desired goals of the system. In this paper we describe our (ECA)2 paradigm for reactive behavior with proactive impact and we present our ongoing work and vision for a system that is capable of context-aware adaptation, while ensuring the maintenance of a set of desired behavioral policies. Our main focus is on developing a formalism that provides tools for expressing normal, as well as defeasible and/or exceptional specification. However, at the same time, we insist on a sound semantics and the capability of answering hypothetical "what-if" queries. Towards this end, we introduce the high-level language that can be used to describe the dynamics of the problem domain, specify triggers under the (ECA)2 paradigm, and reason about the consequences of the possible evolutions.

Original languageEnglish (US)
Title of host publicationActive Conceptual Modeling of Learning - Next Generation Learning-Base System Development
Pages30-46
Number of pages17
DOIs
StatePublished - 2008
Event1st International Active Conceptual Modeling of Learning Workshop - Tucson, AZ, United States
Duration: Nov 8 2006Nov 8 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4512 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Active Conceptual Modeling of Learning Workshop
Country/TerritoryUnited States
CityTucson, AZ
Period11/8/0611/8/06

Funding

★ Research supported by the Northrop Grumman Corp., contract: P.O. 8200082518. ★★ Research supported by the NSF grant, contract: IIS-0325144/003.

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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