Driving Decisions with Business Rules (Tech Target)

Delivering an Active Rules Platform Mark Proctor JBoss Business Rules Project Lead

Delivering Agile, Adaptive, Analytic
Who is Red Hat?
Market leader: Open Source Technology
What is JBoss?
Market leader: Open Source Middleware
What are JBoss Drools and JBoss Enterprise BRMS?
Market leader: Open Source business rules technology
Who is Mark Proctor
Drools Co-creator at Codehaus, joined Jboss in 2005

Integrated Systems Semantic Ontologies Rules Event Processes Workflows Rules Workflows Event Processes Semantic Ontologies

Key Elements in JBoss Enterprise BRMS

JBoss Drools Vs JBoss Enterprise BRMS JBoss Drools
Stand-alone Framework
Innovation
Fast and Frequent Releases
Tested on developer environments
Suitable for development and prototype
No Patches – On to next big thing
Non SLA bound forum support
JBoss Enterprise BRMS
Fully Integrated Platform
Same Innovated Code + Stability + Sanitization
Includes usability, performance and security issues identified during productization
Certified for Multi-OS, Multi-DB
Best for Development and Production
Multi-Year Yr lifecycle
SLA based full support from dedicated support engineers
Open Source Assurance – legal protection
derived

Key Characteristics of a Advanced Hybrid Reasoning Engine
Functional
Relational
Reactive
Hybrid Chaining
Forward and backward
Ontological

Declarative Programming
Production Rule Systems PRD (forward chaining)
Reactive
when Alarm( status == “alert” ) then send( “warning” )
Logic Programming LP (backward chaining)
Query
descendant( “mary”, “jane”)
Functional Programming FP
avg([12, 16, 4, 6]) // Fold
Returns single value 9.5
round([10.3, 4.7, 7.8] ) // Map
Returns List [10, 5, 8]
Description Logic
Person Has Name and LivesAt Address

rule "When there is a fire turn on the sprinkler" when Fire ($room : room) $sprinkler : Sprinkler ( room == $room, on == false ) then modify ( $sprinkler ) { on = true }; println ( "Turn on the sprinkler for room " + $room.name ); end Sample Rules (Fire Alarm)

$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” Sample Rules (Trading System) accumulate ( $s : StockTicker ( symbol == “RHAT” ) over window:time ( 5s ), $avg : avg ( $s.price ), $min : min ( $s.price ), $max : max ( $s.price ) ) eval ( $avg > 55 && $min > 50 && $max < 100 )

Rule Authoring with Eclipse Tools

Guided Editor

Decision Table

Decision Tables – Cell merging.. etc
Cell Merging
Cell Grouping
Typed Columns
Sorting by column
Negate pattern
Support for Ohterwise

Decision Tables – Wizard

Rule Templates

Scenario Testing

Boot Camps – Rules Fest October 2011
URL
http://rulesfest.org/html/home.html
Mon - Wed
Main Conference
Thu - Fri (free)
General Drools Bootcamp (Thu)
Healthcare Focus (Fri)
2011 INTERNATIONAL CONFERENCE ON REASONING TECHNOLOGIES OCTOBER 24-27 ■ HYATT REGENCY – BURLINGAME SAN FRANCISCO, CA

Questions?
Dave Bowman : All right, HAL; I'll go in through the emergency airlock.
HAL : Without your space helmet, Dave, you're going to find that rather difficult.
Dave Bowman : HAL, I won't argue with you anymore! Open the doors!
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?

Upcoming Webinar
Please join us for Part II on September 29th
Active Decisions for the “Aware” Organization And explore how rules and event processing work together
http://www.bitpipe.com/detail/RES/1313509566_69.html

Driving Decisions with Business Rules (Tech Target)

by Mark Proctor

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