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Ontonuts

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Proactive Self-Managed Semantic Web of Things = (we believe) ... Ontonuts triggering MetaRule. Behavior Engine .class {sapl:I sapl:do :nutid} sapl:configuredAs ... – PowerPoint PPT presentation

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Title: Ontonuts


1
Ontonuts
  • Reusable semantic components for multi-agent
    systems

Sergiy Nikitin
Industrial Ontologies Group, University of
Jyväskylä, Finland
2
The paper
3
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
4
What is UBIWARE (in short)
  • 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
  • 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.

5
UBIWARE Architecture
UBIWARE Agent (Live)
Beliefs storage
Roles
Data
.class
RAB
RAB
RAB
RAB
Blackboard
6
S-APL language
  • 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 gt I send Mail
  • Rules (a kind of permanent commitments)
  • John loves Mary gt I send Mail
  • saplis saplRule

7
Early Motivation
  • 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

Data Service
Files
Ontonut Bindings
Ontonuts Role Script
DB/KB
agent-to-agent servicing
adaptation of external sources
8
Example Use case
Expert Agent (Data Service)
Paper Machine Agent
Files
Ontonut Bindings
Ontonuts Role Script
DB/KB
9
Ontonuts architecture
  • Characteristics
  • Three types of call
  • Explicit
  • Goal-based
  • Query-based
  • Planning
  • Backward chaining algorithm
  • Execution
  • Handlers introduced to follow the state of the
    execution and change action plan

Business Logic Script
Ontonut capability
Agent Beliefs (S-APL code)
Ontonuts triggering rule
Ontonuts Role Script
Action Planner
Plan Executor
SQLReader TextTableReader ExcelReader MessageSen
der MessageReceiver
Reusable Atomic Behaviors (Java code)
GoalAnalyser ActionPlanner
Agent Services
Web Service

External resources
10
WP2 Triggering Ontonuts
(UbiBlog)
11
Triggering Ontonuts
12
Ontonut Definition
13
Example call
Experts diary
diary.Entry
entryID
entryDate
author
title
description
position
Query (execution) plan
Scheduled Performance Monitoring
pmon.analysis
analysisID
analysisDate
nodeID
performanceIndex
isautomatic
Alarm History DB
ahist.alarm
alarmID
alarmTime
tag
alarmLimitHigh
alarmLimitLow
value
14
Ontonuts Provision of Dynamic Information
  • An analog of platform-embedded constructs like
  • saplNow saplis ?time (gets current system time)
  • But can be flexibly (re-)defined by user
  • fingridCurrentVoltage saplis ?voltage
  • metsoCurrentOilLevel saplis ?oillevel
  • innowCurrentUsersOnline saplis ?usersonline
  • The approach simplifies the implementation of the
    agents business logic by introducing computable
    elements. The values of these elements are
    computed on-demand (only when a query appears in
    agents beliefs)

15
Provision of Dynamic Information
  • 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 Johns location at the moment
    would look like
  • John currentLocation ?location

16
Conclusions
  • We introduce a unified mechanism for
    componentization within the UBIWARE agent
  • Components can be
  • Internal (do some computations with local
    functions)
  • External (call external sources)
  • Components are
  • Semantic by nature
  • Support goal-driven planning
  • Can be composite (include other components
    within)

17
Thanks
  • Thank you for your attention!
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