Travis Steel

Objectives What is the Agent Paradigm? What is Agent-Oriented Design and how is it different than OO? When to apply AOD techniques? When NOT to apply AOD techniques? MAVs Lab, University of Texas at Dallas 2

Outline Definition of Agent Multi-Agent Systems (MAS) The Agent Paradigm Agent-Oriented Design Domains Conclusion MAVs Lab, University of Texas at Dallas 3

Agent: is an autonomous software entity has objectives to satisfy possesses skills and can offer services possesses resources of its own can communicate, cooperate, coordinate and negotiate directly with other agents acts in an environment that is partially perceived 4 MAVs Lab, University of Texas at Dallas

Example Structure of an Agent 5 MAVs Lab, University of Texas at Dallas Virtual Agent Interaction Module Environment Perception Module Agent Communication Module Task Module Task nTask 1 … Knowledge Module External Knowledge Module Internal Knowledge Module Environment Model Acquaintance Model Self Model Constraints Model Planning & Control Module Control Execution Planning

Multi-Agent System (MAS) A system that consists of a number of agents which interact with one another by exchanging knowledge and by negotiating with each other to achieve their own or some global goal Common Characteristics: non-deterministic distributed adaptive 6 MAVs Lab, University of Texas at Dallas

The Agent Paradigm Programming & Design paradigms: machine code -> prog. languages -> sub-routines -> abstract data types -> objects -> agents Main differences between OOD and AOD: Concept of “Agent” is not limited to a certain application or domain 7 MAVs Lab, University of Texas at Dallas Object-OrientedAgent-Oriented ObjectsAgents NonautonomousAutonomous Interactions are pre-definedConstraints are pre-defined Satisfy RequirementsSatisfying Goals (thus Req’s) Outcome is usually predictableOutcome is usually unpredictable

Agent-Oriented Design 8 MAVs Lab, University of Texas at Dallas Agents are the primary design abstraction Define roles, constraints, and goals Define and coordinate agent roles Assign agent goals that help achieve the system objectives

9 MAVs Lab, University of Texas at Dallas Agent Goal Diagram cite [1]

Agent-Oriented Design AOD is new, so there are many methodologies, and few standards Methodologies and Languages: Agent-UML (FIPA [3] and OMG): extension of UML Agent Communication Language (ACL) Knowledge Query Meta Language (KQML) 10 MAVs Lab, University of Texas at Dallas

Example Patterns for Agent Interaction 11 MAVs Lab, University of Texas at Dallas cite [2] BiddingMatchmaker

Other Differences Between OOD and AOD Object states vs. Agent roles Concurrent & context-based interactions in sequence diagrams Role changes in collaboration diagrams Activity diagrams show how roles effect high-level interaction in various situations Packages can classify agents based on roles or goals Deployment diagrams describe how agents are deployed in their host environment 12 MAVs Lab, University of Texas at Dallas

Domains for MAS Transportation Military Medicine Web Search Finance Social Networking 13 MAVs Lab, University of Texas at Dallas

Conclusion AOD is a strong approach to solving problems that are considered too complex using other approaches. The Agent Paradigm provides an alternate way to conceptualize and design software systems. The Agent Paradigm is not limited to a certain application or domain but can be applied in a variety of circumstances. AOD can simplify complex problems and over-complicate simple problems. 14 MAVs Lab, University of Texas at Dallas

Questions? 15 MAVs Lab, University of Texas at Dallas

References 1. Discussing strategies for software architecting and designing from an Agent-oriented point of view Anna Perini, Angelo Susi 2. Introspecting Agent-Oriented Design Patterns Manuel Kolp, T. Tung Do, Stéphane Faulkner and T. T. Hang Hoang 3. The Foundation for Intelligent Physical Agents: MAVs Lab, University of Texas at Dallas 16