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Drools5 Community Training Module#1: Drools5 BLiP Introduction

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Drools5 Community Training Module#1: Drools5 BLiP Introduction

  1. 1.     Drools5 Community Training Sponsored by Plugtree
  2. 2. Module 1: Drools BLiP Theoretical Introduction Drools5 Community Training version: 1.0-SNAPSHOT Release Date: 03/16/2011 Under The Creative Common License
  3. 3. Module 1: Drools BLiP Theoretical Introduction Drools5 Community Training Course by Mauricio "Salaboy" Salatino and Esteban Aliverti is licensed under a Creative Commons Attribution 3.0 Unported License. Based on a work at salaboy.wordpress. com. Permissions beyond the scope of this license may be available at http: //salaboy.wordpress.com/.
  4. 4. Overview Theoretical Background Drools Business Logic Integration Platform Introduction Drools Expert jBPM5 / Drools Flow Drools Fusion Drools Guvnor
  5. 5. Theoretical Background Artificial Intelligence Expert Systems Knowledge Engineering Inference Engines Rules Based Production Systems Drools History
  6. 6. Artificial Intelligence (AI) "The study and design of intelligent agents." An intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success. The ability of a machine to perform tasks that require human intelligence.
  7. 7. Expert Systems "An expert system is software that attempts to provide an answer to a problem where normally one or more human experts would be consulted." In the begining was replace and now it's assist Software that knows about a specific domain It can solve/answer specific questions
  8. 8. Expert Systems Common Uses of Expert Systems + Medicine -> Diagnosis based on patient symptoms + Field Analysis -> Evaluation of geographical regions (Petrol Prospecting) + Mortgages and Loans -> Used for risk evaluation (scoring)
  9. 9. Knowledge Engineering "Knowledge engineering" is the art and science of observing human experts to build models of their expertise that they can validate.
  10. 10. Inference Engines "An inference engine is a computer program that tries to derive answers from a knowledge base. It is the "brain" that expert systems use to reason to formulate new conclusions for a certain situation."
  11. 11. Inference Engines An inference engine will be in charge of using the formalized knowledge from our expert to answer questions for a specific situation.
  12. 12. Production Systems A production system (or production rule system) are software that are composed of a set of rules about behavior. These rules are a simple and basic representation of knowledge. A production system provides the mechanism to execute actions (behavior) in order to achieve some goal for the system.
  13. 13. Rule If / When / Where / On Conditions Then / Do Actions
  14. 14. Chaining Strategies Methods of Reasoning in Inference Engines Backward Chaining: goal-driven -> Prolog Forward Chaining: data-driven -> Drools
  15. 15. Chaining Strategies Example Scenario: Pet (name == "Fritz", behavior =="croaks") Question: What is the color of my Pet? Rules / Knowledge: 1) When Pet(behavior == "croaks") Then Pet.type = "Frog" 2) When Pet(behavior == "sings") Then Pet.type = "Canary" 3) When Pet(type == "Frog") Then Pet.color = "green" 4) When Pet(type == "Canary") Then Pet.color = "yellow"
  16. 16. Backward Chaining
  17. 17. Forward Chaining
  18. 18. Full Picture
  19. 19. Some characteristics Output answers will contain the justification These kinds of systems are created to support large amounts of knowledge to solve complex situations The knowledge can be: Expressed by Domain Specific users Reused Iteratively improved Maintained decoupled from your application code
  20. 20. Drools History The project was born in '03 Mark Proctor in the project leader Born as an Inference Engine It started using the LEAPS algorithm for pattern matching In Drools 3.x they implemented RETE algorithm In Drools 4.x the RETE algorithm was tuned for high performance
  21. 21. Drools 5 BLiP Named as Business Logic integration Platform (BLiP) Modules: Drools Expert (leader Mark Proctor) jBPM5 / Drools Flow (leader Kris Verlaenen) Drools Fusion (leader Edson Tirelli) Drools Guvnor (leader Toni Rikkola) * There are other experimental modules (Planner, Chance, Grid etc.) that will be not covered here.
  22. 22. Drools Expert The core of Drools Contains the inference engine Uses the RETE algorithm for pattern matching Provides us with a way to create a knowledge base Provides us with a simple API to interact with the inference engine
  23. 23. Business Rule Structure rule "My Rule" <attributes> when <LHS> Person(name == "John") <CEs> then <RHS> System.out.println("Hi John!"); <Actions> end
  24. 24. Drools Expert Common use cases: + Validations + Decision Making + Scoring + Games
  25. 25. jBPM5 Focused on BPM Implements the main stages of the discipline: Model/Design Execute Monitor Pretty close to finish BPMN2 implementation Uses the same APIs that we use in Drools Expert Fully integrated with the inference engine
  26. 26. Business Process Definition: "A sequence of activities, performed by humans or systems to complete a business goal."
  27. 27. Business Process Example New Bank Account process:
  28. 28. Business Process Management Iterative/continuous Discipline Four main stages: Discover Design / Model Execution Monitoring / Improvements / Optimizations
  29. 29. jBPM5 Common use cases In every company Business Processes are used implicitly or explicitly In every business activity In every non-business situation that defines a logical set of activities that needs to be executed/performed
  30. 30. Drools Fusion Focused in Complex Event Processing Temporal reasoning 13 temporal operators (before, after, during, and so on) Enables us to detect complex events (event correlation patterns)
  31. 31. Drools Fusion Big Picture
  32. 32. Drools Fusion Temporal Operators Table
  33. 33. Drools Fusion Common use cases: Fraud Detection Stock Trading Hardware monitoring Transport and Logistics Everywhere we need to correlate or aggregate events
  34. 34. Drools Guvnor Commonly tagged as a BRMS Centralized Knowledge Repository (JCR) Handles the Knowledge versioning and categorization Now it includes more User Friendly features like: Guided Rules Authoring Test Cases Creation Rule Constraints Meta-Model Rule Validation and Verification Business Process Modeling
  35. 35. Drools Guvnor Guided Editor:
  36. 36. Briefing Up Covered Topics: Conceptual background of Drools Project Drools Main Modules Introduction
  37. 37.     Questions?
  38. 38. Enjoy! Questions and Feedback are always appreciated! Stay Tuned!
  39. 39.     Contact us at www.plugtree.com

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