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JACK Intelligent Agents and Applications

JACK Intelligent Agents and Applications. Hitesh Bhambhani CSE 6362, SPRING 2003 Dr. Lawrence B. Holder. Contents. Introduction to JACK BDI Agents JACK Framework JACK Applications Conclusions and Discussion. Introduction to JACK. Agent Oriented Software, Melbourne, Australia.

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JACK Intelligent Agents and Applications

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  1. JACK Intelligent Agents and Applications Hitesh Bhambhani CSE 6362, SPRING 2003 Dr. Lawrence B. Holder

  2. Contents • Introduction to JACK • BDI Agents • JACK Framework • JACK Applications • Conclusions and Discussion CSE@UTA

  3. Introduction to JACK • Agent Oriented Software, Melbourne, Australia. • JACK Intelligent Agents • Agent oriented development environment built on top of JAVA • Provide developers with a robust, stable, light-weight product • Mainly for use as components of larger environments CSE@UTA

  4. Introduction to JACK • Features • Agent architecture independent facilities • Support for BDI agents • Agent Communication Language (ACL) independent • Geared towards use of middleware and message passing infrastructures • SimpleTeam technology to build agent teams CSE@UTA

  5. BDI Agents • BELIEFS • Description of the state of the world (state as viewed by an agent) • DESIRES/GOALS • Functions that specify the states of the world that are desirable • INTENTIONS/PLANS • A set of actions generated by the agent to change the state of its current environment CSE@UTA

  6. BDI Agents Conceptual Model Environment Beliefs Beliefs Goals ACL Goals Plans Plans Blackboard CSE@UTA

  7. JACK Framework • Extends Java • Keywords to support main concepts e.g. agent, plan, event • Statements for declaration of attributes and characteristics of components • Statements for defining static relations • Statements for agent state manipulation CSE@UTA

  8. JACK Framework • JACK Compiler – JACK Agent Language into Java • JACK Runtime Environment • Execution of JACK agents • Handles communications • Simple agent naming service CSE@UTA

  9. JACK Framework • Agent Development Environment • http://www.agent-software.com/shared/products/images/Design.gif • Agent Debugging Environment • View messages between agents • View internal execution states CSE@UTA

  10. JACK Framework • SimpleTeam Programming • Team oriented programming • Agent collaboration viewed as abstract viewpoint of a group as a whole • Neutral to nature of team structure • Centralized specification of coordinated activity • Achieved through mechanisms of team, role, team capabilities and team plans. CSE@UTA

  11. JACK Applications-ROOBOTS • The Roobots are a team of robots from the University of Melbourne • Entered the small-sized robot league, and finished in fourth place at RoboCup-2002 in Fukuoka, Japan. • Roobots Design uses JACK Agents based on BDI • http://www.cs.mu.oz.au/robocup/2003/F180/html/2001/robots.html CSE@UTA

  12. JACK Applications-Decision Support • Intelligence Preparation for Battlefield • Allocation of surveillance and reconnaissance assets • Planners needed to consider following to plan: • Number and priority of CCIR (Commander’s Critical Information Request) • Nature of surveillance needed to satisfy CCIR • Assets available to plan with • Ongoing availability taken in account priorities, maintenance, etc • Re-plan for developing tactical situation CSE@UTA

  13. JACK Applications-Decision Support • Collection Plan Management System (CPMS) • Planning module based on JACK agents • Visualization module containing Geographical Information System • Database • Terrain data • CCIRs • Surveillance assets (Capabilities, availabilities, etc) CSE@UTA

  14. JACK Applications-Decision Support(CPMS) CSE@UTA

  15. JACK Applications-Decision Support • CPMS planning module • Inputs • List of CCIRs • Order of Battle (ORBAT) • Command and control (C2) structure • Available assets • Current surveillance plan (optional) • Outputs • Set of alternative plans for the commander CSE@UTA

  16. JACK Applications-Decision Support • CPMS planning module implementation • Multi-agent subsystem • Agent hierarchy same as C2 structure • Top level agent prioritizes alternative tasks in CCIRs • Ask subordinate agents for plans • Each subordinate agent applies interdependency constraints to tasks and generates plan CSE@UTA

  17. JACK Applications–Manufacturing Plant • JACK-based holonic manufacturing at the Cambridge Robotic Assembly Cell at Cambridge University, England • A Holon is the combination of a physical process and an intelligent agent • Demo (http://www.agent-software.com/shared/demosNdocs/flashDemos/LongHolonicDemo.html) CSE@UTA

  18. JACK Applications–Defense Simulation • Defense simulations war games - fully scripted scenario where entity activities pre-programmed lacking in modeling humans • Wish to model human roles and their reasoning in a Complex Command and Control (C3) system • Simulation Agent Infrastructure • JACK agents to model human behavior • SimpleTeam used to model entity and group roles and behaviors CSE@UTA

  19. Conclusions • Framework for industrial strength agents • Compatible with various agent architectures and legacy systems • Tool support for design and debugging • However • Not ‘pure’ AI • Current implementations mostly planning apps CSE@UTA

  20. Questions and Discussion CSE@UTA

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