OntonutsOntonuts Reusable semantic components for multi-agent systems Sergiy Nikitin Industrial Ontologies Group, University of Jyväskylä, Finland.

Slides:



Advertisements
Similar presentations
Database System Concepts and Architecture
Advertisements

Formal Semantics for an Abstract Agent Programming Language K.V. Hindriks, Ch. Mayer et al. Lecture Notes In Computer Science, Vol. 1365, 1997
Industrial Ontologies Group University of Jyväskylä Industrial Ontologies Group.
Mastering Intelligent Clouds Engineering Intelligent Data Processing Services in the Cloud Sergiy Nikitin, Industrial Ontologies Group, University of Jyväskylä,
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 12 Slide 1 Distributed Systems Design 2.
Industrial Ontologies Group University of Jyväskylä PRIME Project Idea “Proactive Inter-Middleware for Self- Configurable Heterogeneous Cloud Ecosystems”
1 On Death, Taxes, & the Convergence of Peer-to-Peer & Grid Computing Adriana Iamnitchi Duke University “Our Constitution is in actual operation; everything.
0 General information Rate of acceptance 37% Papers from 15 Countries and 5 Geographical Areas –North America 5 –South America 2 –Europe 20 –Asia 2 –Australia.
Nadia Ranaldo - Eugenio Zimeo Department of Engineering University of Sannio – Benevento – Italy 2008 ProActive and GCM User Group Orchestrating.
Object-Oriented Analysis and Design
Variability Oriented Programming – A programming abstraction for adaptive service orientation Prof. Umesh Bellur Dept. of Computer Science & Engg, IIT.
Adding Organizations and Roles as Primitives to the JADE Framework NORMAS’08 Normative Multi Agent Systems, Matteo Baldoni 1, Valerio Genovese 1, Roberto.
Semantic Web Services for Smart Devices based on Mobile Agents Vagan Terziyan Industrial Ontologies Group University of Jyväskylä
SOFIA: Agent Scenario for Forest Industry Tailoring UBIWARE Platform Towards Industrial Agent- driven Solutions Sergiy Nikitin, Industrial Ontologies Group,
Industrial Ontologies Group University of Jyväskylä UBIWARE: UBIWARE: “Device” “Expert” “Service” Resource Agent “Smart Semantic Middleware for the Internet.
University of Jyväskylä Artem Katasonov, PhD University of Jyväskylä, Finland Visit to MIT.
On management aspects of future ICT systems Associate Professor Evgeny Osipov Head of Dependable Communication and Computation group Luleå University of.
Industrial Ontologies Group: our history and team Vagan Terziyan, Group Leader Industrial Ontologies Group Agora Center, University of Jyväskylä.
P2P as a Discovery Instrument for Multi-Agent Ubiquitous Middleware P2P as a Discovery Instrument for Multi-Agent Ubiquitous Middleware A work-package.
SmartResource: Proactive Self-Maintained Resources in Semantic Web TEKES Project proposal Vagan Terziyan, Project Leader Industrial Ontologies Group Agora.
DATA INTEGRATION SOLUTION FOR PAPER INDUSTRY Industrial Ontologies Group University of Jyväskylä Motivating scenario ! Customer Site (maintenance support)
Industrial Ontologies Group University of Jyväskylä CONTEXT-POLICY-CONFIGURATION: Paradigm of Intelligent Autonomous System Creation Oleksiy Khriyenko.
Introduction to Agent Technology in Mobile Environment Course Introduction Vagan Terziyan Department of Mathematical Information Technology University.
23/03/2007 mail-to: site: A Security Framework for Smart Ubiquitous.
Information Retrieval in Distributed Environments Based on Context- Aware, Proactive Documents Current Research Information Systems (CRIS 2002) August.
UbiRoad: “Semantic Middleware for Smart Traffic Management”
Industrial Ontologies Group University of Jyväskylä UbiRoad: “Semantic Middleware for Context- Aware Smart Road Environments” “Driver” “Road” “Car” Resource.
Winter Retreat Connecting the Dots: Using Runtime Paths for Macro Analysis Mike Chen, Emre Kıcıman, Anthony Accardi, Armando Fox, Eric Brewer
Chapter 2 Introduction to Systems Architecture. Chapter goals Discuss the development of automated computing Describe the general capabilities of a computer.
University of Jyväskylä Semantic Agent Programming Language (S-APL): A Middleware Platform for the Semantic Web Artem Katasonov and Vagan Terziyan University.
Community Manager A Dynamic Collaboration Solution on Heterogeneous Environment Hyeonsook Kim  2006 CUS. All rights reserved.
Cloud based linked data platform for Structural Engineering Experiment Xiaohui Zhang
Database System Concepts and Architecture Lecture # 3 22 June 2012 National University of Computer and Emerging Sciences.
Katanosh Morovat.   This concept is a formal approach for identifying the rules that encapsulate the structure, constraint, and control of the operation.
©Ian Sommerville 2006Software Engineering, 8th edition. Chapter 12 Slide 1 Distributed Systems Architectures.
An approach to Intelligent Information Fusion in Sensor Saturated Urban Environments Charalampos Doulaverakis Centre for Research and Technology Hellas.
Database System Concepts and Architecture Lecture # 2 21 June 2012 National University of Computer and Emerging Sciences.
95-843: Service Oriented Architecture 1 Master of Information System Management Service Oriented Architecture Lecture 10: Service Component Architecture.
Division of IT Convergence Engineering Towards Unified Management A Common Approach for Telecommunication and Enterprise Usage Sung-Su Kim, Jae Yoon Chung,
Database System Concepts and Architecture
Active Monitoring in GRID environments using Mobile Agent technology Orazio Tomarchio Andrea Calvagna Dipartimento di Ingegneria Informatica e delle Telecomunicazioni.
Assessing the Suitability of UML for Modeling Software Architectures Nenad Medvidovic Computer Science Department University of Southern California Los.
DEVS Namespace for Interoperable DEVS/SOA
AMPol-Q: Adaptive Middleware Policy to support QoS Raja Afandi, Jianqing Zhang, Carl A. Gunter Computer Science Department, University of Illinois Urbana-Champaign.
Contents 1.Introduction, architecture 2.Live demonstration 3.Extensibility.
The Grid System Design Liu Xiangrui Beijing Institute of Technology.
ICCS WSES BOF Discussion. Possible Topics Scientific workflows and Grid infrastructure Utilization of computing resources in scientific workflows; Virtual.
S. Shumilov – Zürich Analytical Visualization Framework - a visual data processing and knowledge discovery system Ivan Denisovich, Serge Shumilov Department.
A Study of Context-Awareness: Gaia & SOCAM Presented by Dongjoo Lee IDS Lab., Seoul National University Gaia: A Middleware Infrastructure to.
GSAF: A Grid-based Services Transfer Framework Chunyan Miao, Wang Wei, Zhiqi Shen, Tan Tin Wee.
Integration of Workflow and Agent Technology for Business Process Management Yuhong Yan. Maamar, Z. Weiming Shen Enterprise Integration Lab.Toronto Univ.Canada.
16/11/ Semantic Web Services Language Requirements Presenter: Emilia Cimpian
1 Technical & Business Writing (ENG-715) Muhammad Bilal Bashir UIIT, Rawalpindi.
Providing web services to mobile users: The architecture design of an m-service portal Minder Chen - Dongsong Zhang - Lina Zhou Presented by: Juan M. Cubillos.
GRID ANATOMY Advanced Computing Concepts – Dr. Emmanuel Pilli.
Status & Challenges Interoperability and global integration of communication infrastructure & service platform Fixed-mobile convergence to achieve a future.
GAS ontology: an ontology for collaboration among ubiquitous computing devices International Journal of Human-Computer Studies (May 2005) Presented By.
1 Ji Wang and Dongsheng Li National Lab for Parallel and Distributed Processing Introduction of iVCE ( Internet-based V irtual C omputing E nvironment.
INTRODUCTION TO GRID & CLOUD COMPUTING U. Jhashuva 1 Asst. Professor Dept. of CSE.
ACGT Architecture and Grid Infrastructure Juliusz Pukacki ‏ EGEE Conference Budapest, 4 October 2007.
Context-Aware Middleware for Resource Management in the Wireless Internet US Lab 신현정.
Real-Time Systems Laboratory Seolyoung, Jeong The CASCADAS Framework for Autonomic Communications Autonomic Communication Springer.
Cloud based linked data platform for Structural Engineering Experiment
Self Healing and Dynamic Construction Framework:
Knowledge Management Systems
Enterprise Computing Collaboration System Example
Web Ontology Language for Service (OWL-S)
Copyright © 2011 Pearson Education, Inc. Publishing as Pearson Addison-Wesley Chapter 2 Database System Concepts and Architecture.
1st International Conference on Semantics, Knowledge and Grid
Towards Unified Management
Presentation transcript:

OntonutsOntonuts Reusable semantic components for multi-agent systems Sergiy Nikitin Industrial Ontologies Group, University of Jyväskylä, Finland

The paper

GUN Concept GUN – Global Understanding eNvironment GUN = Global Environment + Global Understanding = Proactive Self-Managed Semantic Web of Things = ( we believe ) = “Killer Application” for Semantic Web Technology

What is UBIWARE (in short) UBIWARE is a middleware tool to support:UBIWARE is a middleware tool to support:  design and installation of…,  autonomic operation of… and  interoperability among… … complex, heterogeneous, open, dynamic and self- configurable distributed industrial systems;…… complex, heterogeneous, open, dynamic and self- configurable distributed industrial systems;… … and to provide following services for system components:… and to provide following services for system components:  adaptation;  automation;  centralized or P2P organization;  coordination, collaboration, interoperability and negotiation;  self-awareness, communication and observation;  data and process integration;  (semantic) discovery, sharing and reuse.

UBIWARE Architecture.class Blackboard Roles RABRABRAB RAB Beliefs storage UBIWARE Agent (Live) Pool of Atomic Behaviours S-APL repository S-APL Data

S-APL language Key features:Key features:  Interpretable  N3 notation (proposed by Tim-Berners Lee)  Everything is a belief  Containers (“visibility areas” for beliefs)  Statement is a main construct: :John :loves :Mary  Commitment to execute: {:John :loves :Mary} => {:I :send :Mail}  Rules (a kind of permanent commitments) { {:John :loves :Mary} => {:I :send :Mail} } sapl:is sapl:Rule

Distributed Resource Histories: To develop means for an agent to plan and execute composite queries over the distributed sources as if the data from these sources was collected to one virtual graph Early Motivation Agent Beliefs Ontonut Bindings Files Data Service DB/KB agent-to-agent servicing adaptation of external sources Ontonuts Role Script

Example Use case Experts’ diary Scheduled Performance Monitoring Alarm History DB Paper Machine Agent Ontonut Bindings Files Expert Agent (Data Service) DB/KB Ontonuts Role Script

Characteristics: Three types of call:Three types of call: 1.Explicit 2.Goal-based 3.Query-based PlanningPlanning Backward chaining algorithmBackward chaining algorithm ExecutionExecution Handlers introduced to follow the state of the execution and change action planHandlers introduced to follow the state of the execution and change action plan Ontonuts architecture Web Service CSV fileRDBMS Agent Beliefs (S-APL code) SQLReader TextTableReader ExcelReader … MessageSender MessageReceiver Ontonuts Role Script Business Logic Script Reusable Atomic Behaviors (Java code) Excel sheet … Ontonut capability GoalAnalyser ActionPlanner Ontonuts triggering rule Plan Executor Agent Services External resources

WP2: Triggering Ontonuts (UbiBlog) ActivityActivityActivityActivityActivityActivityActivityActivityActivity OntonutOntonutOntonutOntonutOntonutOntonutOntonutOntonutOntonut Live Activity S-APL Ontonut definition: :nutid ont:precondition {A A ?x} :nutid ont:effect {B B ?x} :nutid ont:script {implementation} {B B ?x}=>{?x C C} Ontonuts triggering MetaRule Behavior Engine.class {sapl:I sapl:do :nutid} sapl:configuredAs { x:precondition sapl:is {A A A} } sapl:I ont:haveGoal :id :id ont:haveGoalDef {B B B} (1) (2) (3)

Triggering Ontonuts ActivityActivityActivityActivityActivityActivityActivityActivityActivity OntonutOntonutOntonutOntonutOntonutOntonutOntonutOntonutOntonut Live Activity S-APL Ontonut definition: :nutid ont:precondition {A A ?x} :nutid ont:effect {B B ?x} :nutid ont:script {implementation} {B B ?x}=>{?x C C} Ontonuts triggering MetaRule Behavior Engine.class {sapl:I sapl:do :nutid} sapl:configuredAs { x:precondition sapl:is {A A A} } sapl:I ont:haveGoal :id :id ont:haveGoalDef {B B B} (1) (2) (3)

Ontonut Definition

Example call entryDate diary.Entry author entryID title description position analysisDate pmon.analysis nodeID analysisID performanceIndex isautomatic alarmTime ahist.alarm tag alarmID alarmLimitHigh value Experts’ diary Scheduled Performance Monitoring Alarm History DB alarmLimitLow Query (execution) plan

Ontonuts: Provision of Dynamic Information An analog of platform-embedded constructs like: –sapl:Now sapl:is ?time (gets current system time) But can be flexibly (re-)defined by user –fingrid:CurrentVoltage sapl:is ?voltage –metso:CurrentOilLevel sapl:is ?oillevel –innow:CurrentUsersOnline sapl:is ?usersonline The approach simplifies the implementation of the agent’s business logic by introducing computable elements. The values of these elements are computed on-demand (only when a query appears in agent’s beliefs)The approach simplifies the implementation of the agent’s business logic by introducing computable elements. The values of these elements are computed on-demand (only when a query appears in agent’s beliefs)

Provision of Dynamic Information When extended to more abstract level, computable values can be applied for:When extended to more abstract level, computable values can be applied for:  Counting statistics over dynamically updated data (e.g. average alarm rate per day, or number of students at the lecture now)  Collecting dynamic information about others. E.g. request “what is John’s location at the moment” would look like: :John :currentLocation ?location

ConclusionsConclusions We introduce a unified mechanism for componentization within the UBIWARE agent:We introduce a unified mechanism for componentization within the UBIWARE agent:  Components can be: Internal (do some computations with local functions)Internal (do some computations with local functions) External (call external sources)External (call external sources)  Components are: Semantic by nature Support goal-driven planning Can be composite (include other components within)

ThanksThanks Thank you for your attention!Thank you for your attention!