SlideShare a Scribd company logo
1 of 87
Mark   Proctor Project Lead ,[object Object]
The system goes online on August 4th, 1997.
Human decisions are removed from strategic defense.
SkyNet begins to learn at a geometric rate.
It becomes self-aware at 2:14am Eastern time, August 29th
In a panic, they try to pull the plug.
And, Skynet fights back
Agenda ,[object Object]
Community
History
Unified Concept
Expert
Quick Example
Conditional Elements
Truth Maintenance and Inference
Fusion
Open Source
Business Model
Free as in Free Speech ,[object Object]
Cathedral & the Bazaar ,[object Object]
Given Enough Eyeballs
Release Early, Release Often ,[object Object],[object Object],[object Object]
Open Source ,[object Object]
Flexibility
Control
Academic / Engineering Bridge
Motivations ,[object Object]
Learning/Exploring
Mastery
Being part of Something
Making a difference
Scratching an itch RSA Animate – Drive:  The surprising truth about what motivates us http://www.youtube.com/watch?v=u6XAPnuFjJc
Risk ,[object Object]
Code commits
Number of Developers
% of internal to external developers
Commitment and health of commercial backers
Availability ,[object Object]
Professional services
Hiring
Continued education ,[object Object],[object Object]
Community
Books ,[object Object]
Oh And There are Drools Books Too
Drools Research Network ,[object Object]
Many more as haven't updated
Community Collaboration ,[object Object]
OSDE (Argentina's largest healthcare organisation)
Intalio
Standards ,[object Object]
Director in RuleML group
Sample Industries and Users ,[object Object]
Boot Camps ,[object Object]
Sun, FAMC, OSDE, Kaseya, Fedex, TU Group, Intermountain Healthcare, Gap, Sony Pictures, Lockheed Martin, Kaiser, HP, Wells Fargo, US Navy Research, FOLIOfn, Boeing ..... ,[object Object],[object Object]
5 day event, with 2 days focus on the healthcare industry
OSDE, AT&T, SAIC, US Navy Research, Kaiser, Clinica, Intermountain Healthcare, GE Healthcare, VA, Boeing, Nationwide ....
Communication ,[object Object]
IRC, Internet Relay Chat
History
It All Started Here  Birth of CDSS 1970s 1980s Dendral Baobab Mycin Guidon Neomycin Teiresias Puff Emycin WM Sacon Centaur Wheeze Gravida Clot Oncocin
Because Not Everyone  Is As Smart As He Is
Business Rules Engines 1980s 2010s 1990s 2000s OPS5 ART Clips Jess Drools 2 JRules Drools 3 Drools 4 Drools 5
Drools History ,[object Object]
Iterative improves to JRules syntax with Clips functionality ,[object Object],[object Object]
Basic functional programming feature with “from”
Basic Rule Flow
Basic BRMS ,[object Object],[object Object]
More Advanced Rule Flow integration
Complex Event Process ,[object Object]
Sliding Time Windows ,[object Object]
Unified Vision Behavioural Modelling
Integrated Systems Semantic  Ontologies Rules Event Processes Workflows Rules  Workflows Event Processes Semantic  Ontologies
Integrated Systems ,[object Object]
Semantic Business Ontologies/Taxonomies ,[object Object],[object Object]
Compliments SOA
Unified Vision “ A  common platform  to  model  and  govern  the business  logic  of the enterprise.”
Unified Vision “ A  common platform  to  model  and  govern  the business  logic  of the enterprise.”
Business Logic Lifecycle
jBPM3 File file = new File (“.....”); // file to XML process definition ProcessDefinition processDefinition =  ProcessDefinition.parseXmlString( IoUtils.FileToString( file ) ); ProcessInstance processInstance =  new ProcessInstance(processDefinition); Jess Rete engine = new Rete(); FileReader file = new FileReader("myfile.clp"); Jesp parser = new Jesp(file, engine); parser.parse(false); Esper EPServiceProvider epService = EPServiceProviderManager.getDefaultProvider(); EPStatement countStmt = admin.createEPL( "...." ); countStmt.start(); Knowledge API
Drools Flow KnowledegBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBulider(); kbuilder.addResource(  ResourceFactory.newClassPathResource( “myflow.bpmn2”, ResourceType.BPMN2 ); If ( kbuilder.hasErrors() ) { log.error( kbuilder.hasErrors().toString() ); } KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase(); kbase.addKnowledgePackages( kbase.getKnowledgePackages() ); Knowledge API
Drools Expert KnowledegBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBulider(); kbuilder.addResource(  ResourceFactory.newClassPathResource( “myrules.drl”, ResourceType.DRL ); If ( kbuilder.hasErrors() ) { log.error( kbuilder.hasErrors().toString() ); } KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase(); kbase.addKnowledgePackages( kbase.getKnowledgePackages() ); Knowledge API
<drools:kbase id=&quot;kbase1&quot;> <drools:resource  type=&quot;DRL&quot;  source=&quot;classpath:.../testSpring.drl&quot; /> </drools:kbase> <drools:ksession id=&quot;ksession1&quot; type=&quot; stateless &quot;  kbase =&quot;kbase1&quot; /> <drools:ksession id=&quot;ksession2&quot; type=&quot; stateful &quot;  kbase =&quot;kbase1&quot;/> <camelContext id=&quot;camel&quot;> <route> <from uri=&quot;cxfrs://bean://rsServer&quot;/> <marshal ref=&quot;xstream&quot;/> <to uri=”drools:ksession1” /> <unmarshal ref=&quot;xstream&quot;/> </route> </camelContext> Declarative Services Spring XML and Camel
Event Driven Architectures edBPM + EDM
EDA ,[object Object]
EDA is used to build our sensory system
Rules and processes loosely coupled tightly coupled specific generic Decision Services Process Rules SCOPE COUPLING ?
Key Characteristics ,[object Object]

More Related Content

What's hot

Codestrong 2012 breakout session hacking titanium
Codestrong 2012 breakout session   hacking titaniumCodestrong 2012 breakout session   hacking titanium
Codestrong 2012 breakout session hacking titanium
Axway Appcelerator
 
Wprowadzenie do technologi Big Data i Apache Hadoop
Wprowadzenie do technologi Big Data i Apache HadoopWprowadzenie do technologi Big Data i Apache Hadoop
Wprowadzenie do technologi Big Data i Apache Hadoop
Sages
 

What's hot (20)

Drools and BRMS 6.0 (Dublin Aug 2013)
Drools and BRMS 6.0 (Dublin Aug 2013)Drools and BRMS 6.0 (Dublin Aug 2013)
Drools and BRMS 6.0 (Dublin Aug 2013)
 
Learning Rule Based Programming using Games @DecisionCamp 2016
Learning Rule Based Programming using Games @DecisionCamp 2016Learning Rule Based Programming using Games @DecisionCamp 2016
Learning Rule Based Programming using Games @DecisionCamp 2016
 
Codestrong 2012 breakout session hacking titanium
Codestrong 2012 breakout session   hacking titaniumCodestrong 2012 breakout session   hacking titanium
Codestrong 2012 breakout session hacking titanium
 
Classic Games Development with Drools
Classic Games Development with DroolsClassic Games Development with Drools
Classic Games Development with Drools
 
Wprowadzenie do technologi Big Data i Apache Hadoop
Wprowadzenie do technologi Big Data i Apache HadoopWprowadzenie do technologi Big Data i Apache Hadoop
Wprowadzenie do technologi Big Data i Apache Hadoop
 
Async Redux Actions With RxJS - React Rally 2016
Async Redux Actions With RxJS - React Rally 2016Async Redux Actions With RxJS - React Rally 2016
Async Redux Actions With RxJS - React Rally 2016
 
Wprowadzenie do technologii Big Data / Intro to Big Data Ecosystem
Wprowadzenie do technologii Big Data / Intro to Big Data EcosystemWprowadzenie do technologii Big Data / Intro to Big Data Ecosystem
Wprowadzenie do technologii Big Data / Intro to Big Data Ecosystem
 
Synthesizing API Usage Examples
Synthesizing API Usage Examples Synthesizing API Usage Examples
Synthesizing API Usage Examples
 
Webinar: Building Your First App in Node.js
Webinar: Building Your First App in Node.jsWebinar: Building Your First App in Node.js
Webinar: Building Your First App in Node.js
 
T3chFest2016 - Uso del API JavaScript de Photoshop para obtener fotos HDTR
T3chFest2016 - Uso del API JavaScript de Photoshop para obtener fotos HDTRT3chFest2016 - Uso del API JavaScript de Photoshop para obtener fotos HDTR
T3chFest2016 - Uso del API JavaScript de Photoshop para obtener fotos HDTR
 
HDTR images with Photoshop Javascript Scripting
HDTR images with Photoshop Javascript ScriptingHDTR images with Photoshop Javascript Scripting
HDTR images with Photoshop Javascript Scripting
 
LJC Conference 2014 Cassandra for Java Developers
LJC Conference 2014 Cassandra for Java DevelopersLJC Conference 2014 Cassandra for Java Developers
LJC Conference 2014 Cassandra for Java Developers
 
Mythbusting: Understanding How We Measure the Performance of MongoDB
Mythbusting: Understanding How We Measure the Performance of MongoDBMythbusting: Understanding How We Measure the Performance of MongoDB
Mythbusting: Understanding How We Measure the Performance of MongoDB
 
Cassandra Summit EU 2014 - Testing Cassandra Applications
Cassandra Summit EU 2014 - Testing Cassandra ApplicationsCassandra Summit EU 2014 - Testing Cassandra Applications
Cassandra Summit EU 2014 - Testing Cassandra Applications
 
servlets
servletsservlets
servlets
 
Fault tolerant microservices - LJC Skills Matter 4thNov2014
Fault tolerant microservices - LJC Skills Matter 4thNov2014Fault tolerant microservices - LJC Skills Matter 4thNov2014
Fault tolerant microservices - LJC Skills Matter 4thNov2014
 
Advanced Object-Oriented JavaScript
Advanced Object-Oriented JavaScriptAdvanced Object-Oriented JavaScript
Advanced Object-Oriented JavaScript
 
JavaScript Promises
JavaScript PromisesJavaScript Promises
JavaScript Promises
 
Living with garbage
Living with garbageLiving with garbage
Living with garbage
 
Solr & Lucene @ Etsy by Gregg Donovan
Solr & Lucene @ Etsy by Gregg DonovanSolr & Lucene @ Etsy by Gregg Donovan
Solr & Lucene @ Etsy by Gregg Donovan
 

Viewers also liked

Drools New York City workshop 2011
Drools New York City workshop 2011Drools New York City workshop 2011
Drools New York City workshop 2011
Geoffrey De Smet
 

Viewers also liked (7)

Drools New York City workshop 2011
Drools New York City workshop 2011Drools New York City workshop 2011
Drools New York City workshop 2011
 
Lohit2 : Project to create reusable OpenType tables for complex script fonts
Lohit2 : Project to create reusable OpenType tables for complex script fontsLohit2 : Project to create reusable OpenType tables for complex script fonts
Lohit2 : Project to create reusable OpenType tables for complex script fonts
 
2011-03-29 London - Decision tables in depth (Michael Anstis)
2011-03-29 London - Decision tables in depth (Michael Anstis)2011-03-29 London - Decision tables in depth (Michael Anstis)
2011-03-29 London - Decision tables in depth (Michael Anstis)
 
Drools and jBPM 6 Overview
Drools and jBPM 6 OverviewDrools and jBPM 6 Overview
Drools and jBPM 6 Overview
 
JBoss Application Server 7
JBoss Application Server 7JBoss Application Server 7
JBoss Application Server 7
 
Rule Engine & Drools
Rule Engine & DroolsRule Engine & Drools
Rule Engine & Drools
 
Drools et les moteurs de règles
Drools et les moteurs de règlesDrools et les moteurs de règles
Drools et les moteurs de règles
 

Similar to 2011-03-29 London - drools

Declarative Multilingual Information Extraction with SystemT
Declarative Multilingual Information Extraction with SystemTDeclarative Multilingual Information Extraction with SystemT
Declarative Multilingual Information Extraction with SystemT
Laura Chiticariu
 
Googleappengineintro 110410190620-phpapp01
Googleappengineintro 110410190620-phpapp01Googleappengineintro 110410190620-phpapp01
Googleappengineintro 110410190620-phpapp01
Tony Frame
 
Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...
Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...
Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...
Indus Khaitan
 

Similar to 2011-03-29 London - drools (20)

Buenos Aires Drools Expert Presentation
Buenos Aires Drools Expert PresentationBuenos Aires Drools Expert Presentation
Buenos Aires Drools Expert Presentation
 
JBoss Drools and Drools Fusion (CEP): Making Business Rules react to RTE
JBoss Drools and Drools Fusion (CEP): Making Business Rules react to RTEJBoss Drools and Drools Fusion (CEP): Making Business Rules react to RTE
JBoss Drools and Drools Fusion (CEP): Making Business Rules react to RTE
 
Sparkling Water Webinar October 29th, 2014
Sparkling Water Webinar October 29th, 2014Sparkling Water Webinar October 29th, 2014
Sparkling Water Webinar October 29th, 2014
 
Relevance trilogy may dream be with you! (dec17)
Relevance trilogy  may dream be with you! (dec17)Relevance trilogy  may dream be with you! (dec17)
Relevance trilogy may dream be with you! (dec17)
 
Ztech Connect '19, IBM PureApplication
Ztech Connect '19, IBM PureApplicationZtech Connect '19, IBM PureApplication
Ztech Connect '19, IBM PureApplication
 
CertiFUNcation 2017 Best Practices Extension Development for TYPO3 8 LTS
CertiFUNcation 2017 Best Practices Extension Development for TYPO3 8 LTSCertiFUNcation 2017 Best Practices Extension Development for TYPO3 8 LTS
CertiFUNcation 2017 Best Practices Extension Development for TYPO3 8 LTS
 
Declarative Multilingual Information Extraction with SystemT
Declarative Multilingual Information Extraction with SystemTDeclarative Multilingual Information Extraction with SystemT
Declarative Multilingual Information Extraction with SystemT
 
Big Data Everywhere Chicago: Apache Spark Plus Many Other Frameworks -- How S...
Big Data Everywhere Chicago: Apache Spark Plus Many Other Frameworks -- How S...Big Data Everywhere Chicago: Apache Spark Plus Many Other Frameworks -- How S...
Big Data Everywhere Chicago: Apache Spark Plus Many Other Frameworks -- How S...
 
Open Data and CKAN Data Catalogues
Open Data and CKAN Data CataloguesOpen Data and CKAN Data Catalogues
Open Data and CKAN Data Catalogues
 
Implementing the Genetic Algorithm in XSLT: PoC
Implementing the Genetic Algorithm in XSLT: PoCImplementing the Genetic Algorithm in XSLT: PoC
Implementing the Genetic Algorithm in XSLT: PoC
 
Services for Science
Services for ScienceServices for Science
Services for Science
 
Contract-driven development with OpenAPI 3 and Vert.x | DevNation Tech Talk
Contract-driven development with OpenAPI 3 and Vert.x | DevNation Tech TalkContract-driven development with OpenAPI 3 and Vert.x | DevNation Tech Talk
Contract-driven development with OpenAPI 3 and Vert.x | DevNation Tech Talk
 
Resilience Engineering: A field of study, a community, and some perspective s...
Resilience Engineering: A field of study, a community, and some perspective s...Resilience Engineering: A field of study, a community, and some perspective s...
Resilience Engineering: A field of study, a community, and some perspective s...
 
Googleappengineintro 110410190620-phpapp01
Googleappengineintro 110410190620-phpapp01Googleappengineintro 110410190620-phpapp01
Googleappengineintro 110410190620-phpapp01
 
Compass Framework
Compass FrameworkCompass Framework
Compass Framework
 
New Directions in Metadata
New Directions in MetadataNew Directions in Metadata
New Directions in Metadata
 
Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...
Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...
Creating Interactive Olap Applications With My Sql Enterprise And Mondrian Pr...
 
Computing Outside The Box June 2009
Computing Outside The Box June 2009Computing Outside The Box June 2009
Computing Outside The Box June 2009
 
Agile Data Science
Agile Data ScienceAgile Data Science
Agile Data Science
 
Apache Beam (incubating)
Apache Beam (incubating)Apache Beam (incubating)
Apache Beam (incubating)
 

More from Geoffrey De Smet

What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference
What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev ConferenceWhat is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference
What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference
Geoffrey De Smet
 
2012 02-04 fosdem 2012 - drools planner
2012 02-04 fosdem 2012 - drools planner2012 02-04 fosdem 2012 - drools planner
2012 02-04 fosdem 2012 - drools planner
Geoffrey De Smet
 
Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011
Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011
Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011
Geoffrey De Smet
 
Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)
Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)
Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)
Geoffrey De Smet
 
Open source and business rules
Open source and business rulesOpen source and business rules
Open source and business rules
Geoffrey De Smet
 
Drooling for drools (JBoss webex)
Drooling for drools (JBoss webex)Drooling for drools (JBoss webex)
Drooling for drools (JBoss webex)
Geoffrey De Smet
 
st - demystifying complext event processing
st - demystifying complext event processingst - demystifying complext event processing
st - demystifying complext event processing
Geoffrey De Smet
 
Towards unified knowledge management platform (rulefest 2010)
Towards unified knowledge management platform (rulefest 2010)Towards unified knowledge management platform (rulefest 2010)
Towards unified knowledge management platform (rulefest 2010)
Geoffrey De Smet
 
2010 04-20 san diego bootcamp - drools planner - use cases
2010 04-20 san diego bootcamp - drools planner - use cases2010 04-20 san diego bootcamp - drools planner - use cases
2010 04-20 san diego bootcamp - drools planner - use cases
Geoffrey De Smet
 

More from Geoffrey De Smet (18)

Drools planner - 2012-10-23 IntelliFest 2012
Drools planner - 2012-10-23 IntelliFest 2012Drools planner - 2012-10-23 IntelliFest 2012
Drools planner - 2012-10-23 IntelliFest 2012
 
What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference
What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev ConferenceWhat is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference
What is Drools, Guvnor and Planner? 2012 02-17 Brno Dev Conference
 
2012 02-04 fosdem 2012 - drools planner
2012 02-04 fosdem 2012 - drools planner2012 02-04 fosdem 2012 - drools planner
2012 02-04 fosdem 2012 - drools planner
 
JUDCon London 2011 - Bin packing with drools planner by example
JUDCon London 2011 - Bin packing with drools planner by exampleJUDCon London 2011 - Bin packing with drools planner by example
JUDCon London 2011 - Bin packing with drools planner by example
 
Drools Planner webinar (2011-06-15): Drools Planner optimizes automated planning
Drools Planner webinar (2011-06-15): Drools Planner optimizes automated planningDrools Planner webinar (2011-06-15): Drools Planner optimizes automated planning
Drools Planner webinar (2011-06-15): Drools Planner optimizes automated planning
 
Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011
Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011
Applying CEP Drools Fusion - Drools jBPM Bootcamps 2011
 
2011-03-29 London - Why do I need the guvnor BRMS?
2011-03-29 London - Why do I need the guvnor BRMS?2011-03-29 London - Why do I need the guvnor BRMS?
2011-03-29 London - Why do I need the guvnor BRMS?
 
2011-03-09 London - Drools Planner in a nutshell
2011-03-09 London - Drools Planner in a nutshell2011-03-09 London - Drools Planner in a nutshell
2011-03-09 London - Drools Planner in a nutshell
 
2011-03-24 IDC - Adaptive and flexible processes (Mark Proctor)
2011-03-24 IDC - Adaptive and flexible processes (Mark Proctor)2011-03-24 IDC - Adaptive and flexible processes (Mark Proctor)
2011-03-24 IDC - Adaptive and flexible processes (Mark Proctor)
 
Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)
Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)
Pushing the rule engine to its limits with drools planner (parisjug 2010-11-09)
 
Open source and business rules
Open source and business rulesOpen source and business rules
Open source and business rules
 
Drooling for drools (JBoss webex)
Drooling for drools (JBoss webex)Drooling for drools (JBoss webex)
Drooling for drools (JBoss webex)
 
st - demystifying complext event processing
st - demystifying complext event processingst - demystifying complext event processing
st - demystifying complext event processing
 
jBPM 5 (JUDCon 2010-10-08)
jBPM 5 (JUDCon 2010-10-08)jBPM 5 (JUDCon 2010-10-08)
jBPM 5 (JUDCon 2010-10-08)
 
Applying complex event processing (2010-10-11)
Applying complex event processing (2010-10-11)Applying complex event processing (2010-10-11)
Applying complex event processing (2010-10-11)
 
Towards unified knowledge management platform (rulefest 2010)
Towards unified knowledge management platform (rulefest 2010)Towards unified knowledge management platform (rulefest 2010)
Towards unified knowledge management platform (rulefest 2010)
 
2010 04-20 san diego bootcamp - drools planner - use cases
2010 04-20 san diego bootcamp - drools planner - use cases2010 04-20 san diego bootcamp - drools planner - use cases
2010 04-20 san diego bootcamp - drools planner - use cases
 
Drools BeJUG 2010
Drools BeJUG 2010Drools BeJUG 2010
Drools BeJUG 2010
 

Recently uploaded

“Iamnobody89757” Understanding the Mysterious of Digital Identity.pdf
“Iamnobody89757” Understanding the Mysterious of Digital Identity.pdf“Iamnobody89757” Understanding the Mysterious of Digital Identity.pdf
“Iamnobody89757” Understanding the Mysterious of Digital Identity.pdf
Muhammad Subhan
 

Recently uploaded (20)

ChatGPT and Beyond - Elevating DevOps Productivity
ChatGPT and Beyond - Elevating DevOps ProductivityChatGPT and Beyond - Elevating DevOps Productivity
ChatGPT and Beyond - Elevating DevOps Productivity
 
Generative AI Use Cases and Applications.pdf
Generative AI Use Cases and Applications.pdfGenerative AI Use Cases and Applications.pdf
Generative AI Use Cases and Applications.pdf
 
WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024
 
Oauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoftOauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoft
 
UiPath manufacturing technology benefits and AI overview
UiPath manufacturing technology benefits and AI overviewUiPath manufacturing technology benefits and AI overview
UiPath manufacturing technology benefits and AI overview
 
How we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdfHow we scaled to 80K users by doing nothing!.pdf
How we scaled to 80K users by doing nothing!.pdf
 
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
Human Expert Website Manual WCAG 2.0 2.1 2.2 Audit - Digital Accessibility Au...
 
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
 
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
Event-Driven Architecture Masterclass: Integrating Distributed Data Stores Ac...
 
“Iamnobody89757” Understanding the Mysterious of Digital Identity.pdf
“Iamnobody89757” Understanding the Mysterious of Digital Identity.pdf“Iamnobody89757” Understanding the Mysterious of Digital Identity.pdf
“Iamnobody89757” Understanding the Mysterious of Digital Identity.pdf
 
ADP Passwordless Journey Case Study.pptx
ADP Passwordless Journey Case Study.pptxADP Passwordless Journey Case Study.pptx
ADP Passwordless Journey Case Study.pptx
 
Google I/O Extended 2024 Warsaw
Google I/O Extended 2024 WarsawGoogle I/O Extended 2024 Warsaw
Google I/O Extended 2024 Warsaw
 
Continuing Bonds Through AI: A Hermeneutic Reflection on Thanabots
Continuing Bonds Through AI: A Hermeneutic Reflection on ThanabotsContinuing Bonds Through AI: A Hermeneutic Reflection on Thanabots
Continuing Bonds Through AI: A Hermeneutic Reflection on Thanabots
 
Using IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & IrelandUsing IESVE for Room Loads Analysis - UK & Ireland
Using IESVE for Room Loads Analysis - UK & Ireland
 
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - QuestionnaireMicrosoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - Questionnaire
 
Design and Development of a Provenance Capture Platform for Data Science
Design and Development of a Provenance Capture Platform for Data ScienceDesign and Development of a Provenance Capture Platform for Data Science
Design and Development of a Provenance Capture Platform for Data Science
 
The Metaverse: Are We There Yet?
The  Metaverse:    Are   We  There  Yet?The  Metaverse:    Are   We  There  Yet?
The Metaverse: Are We There Yet?
 
ERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage IntacctERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage Intacct
 
Portal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russePortal Kombat : extension du réseau de propagande russe
Portal Kombat : extension du réseau de propagande russe
 
Syngulon - Selection technology May 2024.pdf
Syngulon - Selection technology May 2024.pdfSyngulon - Selection technology May 2024.pdf
Syngulon - Selection technology May 2024.pdf
 

2011-03-29 London - drools

  • 1.
  • 2. The system goes online on August 4th, 1997.
  • 3. Human decisions are removed from strategic defense.
  • 4. SkyNet begins to learn at a geometric rate.
  • 5. It becomes self-aware at 2:14am Eastern time, August 29th
  • 6. In a panic, they try to pull the plug.
  • 8.
  • 19.
  • 20.
  • 22.
  • 23.
  • 27.
  • 30. Being part of Something
  • 32. Scratching an itch RSA Animate – Drive: The surprising truth about what motivates us http://www.youtube.com/watch?v=u6XAPnuFjJc
  • 33.
  • 36. % of internal to external developers
  • 37. Commitment and health of commercial backers
  • 38.
  • 41.
  • 43.
  • 44. Oh And There are Drools Books Too
  • 45.
  • 46. Many more as haven't updated
  • 47.
  • 48. OSDE (Argentina's largest healthcare organisation)
  • 50.
  • 52.
  • 53.
  • 54.
  • 55. 5 day event, with 2 days focus on the healthcare industry
  • 56. OSDE, AT&T, SAIC, US Navy Research, Kaiser, Clinica, Intermountain Healthcare, GE Healthcare, VA, Boeing, Nationwide ....
  • 57.
  • 60. It All Started Here Birth of CDSS 1970s 1980s Dendral Baobab Mycin Guidon Neomycin Teiresias Puff Emycin WM Sacon Centaur Wheeze Gravida Clot Oncocin
  • 61. Because Not Everyone Is As Smart As He Is
  • 62. Business Rules Engines 1980s 2010s 1990s 2000s OPS5 ART Clips Jess Drools 2 JRules Drools 3 Drools 4 Drools 5
  • 63.
  • 64.
  • 65. Basic functional programming feature with “from”
  • 67.
  • 68. More Advanced Rule Flow integration
  • 69.
  • 70.
  • 72. Integrated Systems Semantic Ontologies Rules Event Processes Workflows Rules Workflows Event Processes Semantic Ontologies
  • 73.
  • 74.
  • 76. Unified Vision “ A common platform to model and govern the business logic of the enterprise.”
  • 77. Unified Vision “ A common platform to model and govern the business logic of the enterprise.”
  • 79. jBPM3 File file = new File (“.....”); // file to XML process definition ProcessDefinition processDefinition = ProcessDefinition.parseXmlString( IoUtils.FileToString( file ) ); ProcessInstance processInstance = new ProcessInstance(processDefinition); Jess Rete engine = new Rete(); FileReader file = new FileReader(&quot;myfile.clp&quot;); Jesp parser = new Jesp(file, engine); parser.parse(false); Esper EPServiceProvider epService = EPServiceProviderManager.getDefaultProvider(); EPStatement countStmt = admin.createEPL( &quot;....&quot; ); countStmt.start(); Knowledge API
  • 80. Drools Flow KnowledegBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBulider(); kbuilder.addResource( ResourceFactory.newClassPathResource( “myflow.bpmn2”, ResourceType.BPMN2 ); If ( kbuilder.hasErrors() ) { log.error( kbuilder.hasErrors().toString() ); } KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase(); kbase.addKnowledgePackages( kbase.getKnowledgePackages() ); Knowledge API
  • 81. Drools Expert KnowledegBuilder kbuilder = KnowledgeBuilderFactory.newKnowledgeBulider(); kbuilder.addResource( ResourceFactory.newClassPathResource( “myrules.drl”, ResourceType.DRL ); If ( kbuilder.hasErrors() ) { log.error( kbuilder.hasErrors().toString() ); } KnowledgeBase kbase = KnowledgeBaseFactory.newKnowledgeBase(); kbase.addKnowledgePackages( kbase.getKnowledgePackages() ); Knowledge API
  • 82. <drools:kbase id=&quot;kbase1&quot;> <drools:resource type=&quot;DRL&quot; source=&quot;classpath:.../testSpring.drl&quot; /> </drools:kbase> <drools:ksession id=&quot;ksession1&quot; type=&quot; stateless &quot; kbase =&quot;kbase1&quot; /> <drools:ksession id=&quot;ksession2&quot; type=&quot; stateful &quot; kbase =&quot;kbase1&quot;/> <camelContext id=&quot;camel&quot;> <route> <from uri=&quot;cxfrs://bean://rsServer&quot;/> <marshal ref=&quot;xstream&quot;/> <to uri=”drools:ksession1” /> <unmarshal ref=&quot;xstream&quot;/> </route> </camelContext> Declarative Services Spring XML and Camel
  • 84.
  • 85. EDA is used to build our sensory system
  • 86. Rules and processes loosely coupled tightly coupled specific generic Decision Services Process Rules SCOPE COUPLING ?
  • 87.
  • 92.
  • 93.
  • 94.
  • 95.
  • 96.
  • 97. Drools Trunk has a prototype Prolog like query backward chaining capabilities. Stronger Polog like capabilities planned.
  • 98.
  • 99. Drools 5.0 has some functional capabilities
  • 100. Drools 5.1, 5.2 will be looking to have strong functional capabilities Hybrid Logic Engine
  • 101.
  • 102. Planned, See “The Future” Hybrid Logic Engine
  • 103.
  • 106. POSL - Positional-Slotted Language
  • 108. Maps and Arrays (Collections)
  • 109. Collections and XPath like filtering
  • 111. Managed Object Graphs (MOGS)
  • 113. Queries and Unification
  • 115.
  • 117. Accumulate Improvements to Support Haskell map/fold/filter and MVEL projection/fold
  • 125. Opportunistic Backward Chaining, Lazy Field/Object Values
  • 126. ...
  • 129. rule “increase balance for AccountPeriod Credits” when ap : AccountPeriod() acc : Account( $accountNo : accountNo ) CashFlow( type == CREDIT, accountNo == $accountNo, date >= ap.start && <= ap.end, $ammount : ammount ) then acc.balance += $amount; end select * from Account acc, Cashflow cf, AccountPeriod ap where acc.accountNo == cf.accountNo and cf.type == CREDIT cf.date >= ap.start and cf.date <= ap.end trigger : acc.balance += cf.amount Credit Cashflow Rule
  • 130. rule “increase balance for AccountPeriod Credits” when ap : AccountPeriod() acc : Account( $accountNo : accountNo ) CashFlow( type == CREDIT, accountNo == $accountNo, date >= ap.start && <= ap.end, $ammount : ammount ) then acc.balance += $amount; end rule “decrease balance for AccountPeriod Debits” when ap : AccountPeriod() acc : Account( $accountNo : accountNo ) CashFlow( type == DEBIT, accountNo == $accountNo, date >= ap.start && <= ap.end, $ammount : ammount ) then acc.balance -= $amount; end Rules as a “view”
  • 131. Drools Expert Quick Example Stateless
  • 132. Definitions public class Applicant { private String name; private int age; private boolean valid; // getter and setter methods here } rule &quot;Is of valid age&quot; when $a : Applicant( age < 18 ) then modify ( $a ) { valid = false }; ends
  • 133. Building KnowledgeBuilder kbuilder = KnowledgeBuilderFactory .newKnowledgeBuilder(); kbuilder .add( ResourceFactory .newClassPathResource( &quot;licenseApplication.drl&quot; , getClass() ), ResourceType.DRL ); if ( kbuilder .hasErrors() ) { System.err.println( kbuilder .getErrors().toString() ); } kbase .addKnowledgePackages( kbuilder .getKnowledgePackages() );
  • 134. Executing StatelessKnowledgeSession ksession = kbase .newStatelessKnowledgeSession(); Applicant applicant = new Applicant ( &quot;Mr John Smith&quot; , 16 ); assertTrue ( applicant .isValid() ); ksession .execute( applicant ); assertFalse ( applicant .isValid() ); rule &quot;Is of valid age&quot; when $a : Applicant( age < 18 ) then modify ( $a ) { valid = false }; ends
  • 135. Drools Expert Quick Example Stateful
  • 136. Definitions public class Room { private String name // getter and setter methods here } public class Sprinkler { private Room room ; private boolean on ; // getter and setter methods here } public class Fire { private Room room ; // getter and setter methods here } public class Alarm { }
  • 137. Definitions rule &quot;When there is a fire turn on the sprinkler&quot; when Fire ($room : room) $sprinkler : Sprinkler ( room == $room, on == false ) then modify ( $sprinkler ) { on = true }; println ( &quot;Turn on the sprinkler for room &quot; + $room.name ); end rule &quot;When the fire is gone turn off the sprinkler&quot; when $room : Room ( ) $sprinkler : Sprinkler ( room == $room, on == true ) not Fire ( room == $room ) then modify ( $sprinkler ) { on = false }; println ( &quot;Turn off the sprinkler for room &quot; + $room.name ); end
  • 138. Definitions rule &quot;Raise the alarm when we have one or more fires&quot; when exists Fire () then insert ( new Alarm () ); println ( &quot;Raise the alarm&quot; ); end rule &quot;Cancel the alarm when all the fires have gone&quot; when not Fire () $alarm : Alarm () then retract ( $alarm ); println ( &quot;Cancel the alarm&quot; ); end
  • 139. Definitions rule &quot;Status output when things are ok&quot; when not Alarm () not Sprinkler ( on === true ) then println ( &quot;Everything is ok&quot; ); end
  • 140. Executing String [] names = new String []{ &quot;kitchen&quot; , &quot;bedroom&quot; , &quot;office&quot; , &quot;livingroom&quot; }; Map < String , Room > name2room = new HashMap < String , Room >(); for ( String name : names ){ Room room = new Room ( name ); name2room .put( name , room ); ksession .insert( room ); Sprinkler sprinkler = new Sprinkler ( room ); ksession .insert( sprinkler ); } ksession .fireAllRules() > Everything is ok
  • 141. Executing Fire kitchenFire = new Fire ( name2room.get( &quot;kitchen&quot; ) ); Fire officeFire = new Fire ( name2room.get( &quot;office&quot; ) ); FactHandle kitchenFireHandle = ksession .insert( kitchenFire ); FactHandle officeFireHandle = ksession .insert( officeFire ); ksession .fireAllRules(); > Raise the alarm > Turn on the sprinkler for room kitchen > Turn on the sprinkler for room office
  • 142. Executing ksession .retract( kitchenFireHandle ); ksession .retract( officeFireHandle ); ksession .fireAllRules() > Turn off the sprinkler for room office > Turn off the sprinkler for room kitchen > Cancel the alarm > Everything is ok rule &quot;Status output when things are ok&quot; when not Alarm () not Sprinkler ( on === true ) then println ( &quot;Everything is ok&quot; ); end
  • 144. not Bus( color = “red” ) Conditional Elements exists Bus( color = “red” ) forall ( $bus : Bus( floors == 2 ) Bus( this == $bus, color == “red” ) ) forall ( $bus : Bus( color == “red” ) )
  • 145. Accumulate CE rule &quot;accumulate&quot; when $sum : Number( intValue > 100 ) from accumulate ( Bus( color == &quot;red&quot; , $t : takings ) sum( $t ) ) then print &quot;sum is “ + $sum; end
  • 146. Accumulate CE Patterns and CE's can be chained with ' from ' rule &quot;collect&quot; when $zipCode : ZipCode() $sum : Number( intValue > 100 ) from accumulate ( Bus( color == &quot;red&quot; , $t : takings ) from $hbn.getNamedQuery( “Find Buses” ) .setParameters( [ “zipCode” : $zipCode ] ) .list(), sum( $t ) ) then print &quot;sum is “ + $sum; end
  • 148. Timers rule “name” timer 1m30s when $l : Light( status == “on” ) then modify ( $l ) { status = “off” }; rule “name” timer (int: 1m30s 0) when $l : Light( status == “on” ) then modify ( $l ) { status = “off” }; When the light is on, and has been on for 1m30s then turn it off Same as above. Interval timer with JDK semantics for initial duration, then repeat duration.
  • 149. Timers rule “name” timer ( cron: 0 0/15 * * * * ) when Alarm( ) then sendEmail( ”Alert Alert Alert!!!” ) Field Name Mandatory? Allowed Values Allowed Special Characters Seconds YES 0-59 , - * / Minutes YES 0-59 , - * / Hours YES 0-23 , - * / Day of month YES 1-31 , - * ? / L W Month YES 1-12 or JAN-DEC , - * / Day of week YES 1-7 or SUN-SAT , - * ? / L # Year NO empty, 1970-2099 , - * / Send alert every quarter of an hour
  • 150. Calendars rule &quot;weekdays are high priority&quot; calendars &quot;weekday&quot; timer (int:0 1h) when Alarm() then send( &quot;priority high - we have an alarm” ); end rule &quot;weekend are low priority&quot; calendars &quot;weekend&quot; timer (int:0 4h) when Alarm() then send( &quot;priority low - we have an alarm” ); end Execute now and after 1 hour duration Execute now and after 4 hour duration
  • 152. TMS and Inference rule &quot;Issue Child Bus Pass&quot; when $p : Person ( age < 16 ) then insert(new ChildBusPass ( $p ) ); end rule &quot;Issue Adult Bus Pass&quot; when $p : Person ( age >= 16 ) then insert(new AdultBusPass ( $p ) ); end Couples the logic What happens when the Child stops being 16?
  • 153.
  • 154. Leaky
  • 155. Brittle integrity - manual maintenance
  • 156.
  • 157. When the rule is no longer true, the object is retracted. when $p : Person ( age < 16 ) then logicalInsert ( new IsChild ( $p ) ) end when $p : Person ( age >= 16 ) then logicalInsert ( new IsAdult ( $p ) ) end de-couples the logic Maintains the truth by automatically retracting
  • 158. TMS and Inference rule &quot;Issue Child Bus Pass&quot; when $p : Person ( ) IsChild ( person =$p ) then logicalInsert ( new ChildBusPass ( $p ) ); end rule &quot;Issue Adult Bus Pass&quot; when $p : Person ( age >= 16 ) IsAdult ( person =$p ) then logicalInsert ( new AdultBusPass ( $p ) ); end The truth maintenance cascades
  • 159. TMS and Inference rule &quot;Issue Child Bus Pass&quot; when $p : Person ( ) not ( ChildBusPass ( person == $p ) ) then requestChildBusPass( $p ); end The truth maintenance cascades
  • 160.
  • 162. Provide semantic abstractions for those encapsulation
  • 163. Integrity robustness – truth maintenance
  • 164. Fusion
  • 165.
  • 166.
  • 167.
  • 170.
  • 173. $c : Custumer( type == “VIP ) $oe : BuyOrderEvent( customer == $c ) from entry-point “Home Broker Stream” not BuyAckEvent( relatedEvent == $oe.id, this after[1s, 10s] $oe ) from entry-point “Stock Trader Stream” Operators Existing Drools 'not' Conditional Elements can be used to detect non-occurrence of events BackAckEvent must occur between 1s and 10s ' after' BuyOrderEvent
  • 174. Aggregations Rule Engines do not deal with aggregations $n : Number( intValue > 100 ) from accumulate ( $s : StockTicker( symbol == “RHAT” ) over window:time ( 5s ), average ( $s.price ) ) Over 5 seconds Aggregate ticker price for RHAT over last 5 seconds The pattern 'Number' reasons 'from' the accumulate result
  • 175. CEP Applied at FedEx Custom Critical * Presented by Adam Mollemkopf at ORF 2009
  • 176. CEP Applied at FedEx Custom Critical * Presented by Adam Mollemkopf at ORF 2009
  • 177.
  • 178.
  • 179.
  • 180.
  • 181.
  • 182.
  • 183.
  • 184. HAL : Without your space helmet, Dave, you're going to find that rather difficult.
  • 185. Dave Bowman : HAL, I won't argue with you anymore! Open the doors!
  • 186. HAL : Dave, this conversation can serve no purpose anymore. Goodbye. Joshua: Greetings, Professor Falken. Stephen Falken : Hello, Joshua. Joshua: A strange game. The only winning move is not to play. How about a nice game of chess?