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Component-Based Modeling of Intelligent Agents in HLA Environment

This project focuses on developing an efficient approach for creating agent behavior by using a component-based modeling tool in an HLA environment. The goal is to support knowledge acquisition, behavior modeling, code generation, and validation of intelligent agents. The approach aims to improve the development process and facilitate the reuse of existing physical models for adding agent behavior.

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Component-Based Modeling of Intelligent Agents in HLA Environment

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  1. Modeling Component-Based Intelligent Agents in an HLA-Environment using an Agent Development Tool Jennie Byström Magnus Johansson Staffan Löf Pitch AB

  2. Outline • Problem Identification • Project Focus • Definitions – agents, components • Characteristics of Agent Factory • Summary

  3. Problem Definition • Increasing demand on realistic agent behavior • Hard and time-consuming to develop agents • Development of agent environment takes time • Difficult to change ”coded” behavior as opposed to modeled behavior • There is a desire to reuse existing physical models and add agent behavior

  4. Project Focus • Develop an approach to make the task of creating agent behavior more efficient • Focus on the SME – support the knowledge acquisition process • Consider the complete chain of activities • Behavior modeling • ”Situatedness” • Code generation • Executing/verifying/validation behavior • Use a component-based approach for agent composition

  5. Intelligent Agents - Definition An entity that resides in environments where it interprets ”sensor” data that reflect events in the environment and executes ”motor” commands that produce effects in the environment – FIPA’97

  6. Outside World response stimuli Sensory System Motor System KB Procedural Knowledge Fact Knowledge Cognition Agent Intelligent Agents - Concept

  7. Components • A piece of self-contained software designed for a specific purpose • Exposed through an interface • Designed to be combined and collaborate with other components • Easily interchangeable • Federates are components in an HLA-federation

  8. Characteristics of Agent Factory • Goal-oriented knowledge representation • Rule-based structure for behavior representation • Provides a graphical modeling approach to agents • Provides a predefined, standardized, component-based framework for agents • Domain-independent • Generation of Java-agents

  9. Knowledge Architecture • Goal-oriented behavior • Affects the outside world • Goal-plan-phase structure • Reactive knowledge • Affects the outside world • Reacts on changes in the outside world • Common knowledge • Expands the fact knowledge • Reacts on changes in the outside world • Fact knowledge • The agent beliefs

  10. Goal Sub-goal-1 Sub-goal-2 Plan-1 Plan-2 Sub-goal-3 Sub-goal-4 Phase-1 Phase-3 Phase-2 Phase-4 Phase-5 Plan-3 Plan-4 ... ... Phase-6 Phase-8 Phase-7 Phase-9 Phase-10 Goal-oriented Behavior

  11. Modeling Agent Behavior • Graphical representation of the reasoning behavior

  12. IF targetWithinFireRange THEN fireMissileAtTarget int dx = target.getX() - pilot.getVehicle().getX(); int dy = target.getY() - pilot.getVehicle().getY(); int distance = Math.sqrt(dx * dx + dy * dy); return (distance < 55); Rule Components • Abstraction of conditions and actions • SME-level of the knowledge • Increases reusability and readability of the behavior

  13. Creating and using Rule Components • Graphical construction of rules • Drag and drop to used specified rule components in rules

  14. Agent Sensory system Motor system Sensory system Motor system pRTI Behavior system HLA as Agent Framework • pRTI is used as infrastructure within the agent to connect the behavior component with sensory and motor systems • Component-based approach • Sensory and motor systems becomes more easily exchangeable

  15. Federate Federate pRTI Sensory system Motor system Sensory system Motor system pRTI Behavior system Agent federate Agent Federate • The agent federate hosts an internal federation and participates in an external federation • The sensory and motor systems act as filter between the two

  16. SME- knowledge AgentFactory Behavior Modeling HLA- compliance Intermediate Format Conceptual model SOM FOM Knowledge Representation Back-end Front-end Code Generation • Generates code to integrate the specified motor and sensory systems with the behavior component in an agent federate • Two-phase generation

  17. Validating Behavior • Face Validation • Transparent Agents

  18. Agent Factory Internal Knowledge Space Repository Behavior Editor Agent Composition Code Generator Agent Factory – Overall Architecture

  19. Summary • Agent Factory is an initial approach to support effective development of agent behavior • Graphical tool to support symbolic modeling of behavior knowledge • HLA is used as technical framework • Code generation techniques to automatically generate HLA-compliant federates hosting agents

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