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Lecture 14 Multi-Agent Systems

Lecture 14 Multi-Agent Systems. Topics Basics MAS Architectures Coordination KQML Collaboration CNP Development of MAS Applications. Basics. Basics. MAS as seen from Distributed AI

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Lecture 14 Multi-Agent Systems

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  1. Lecture 14 Multi-Agent Systems • Topics • Basics • MAS Architectures • Coordination • KQML • Collaboration • CNP • Development of MAS • Applications

  2. Basics

  3. Basics • MAS as seen from Distributed AI • a loosely coupled network of entities that work together to find answers to problems that are beyond the individual capabilities or knowledge of each entity. • A more general meaning • systems composed of autonomous components that exhibit the following characteristics: • each agent has incomplete capabilities to solve a problem • there is no global system control • data is decentralized • computation is asynchronous

  4. Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents Basics Traditional Software • Traditional • Client-server • Low-level messages • Synchronous • Can not do the job! • Agent breakthroughs • Peer-to-peer topology • Blackboard coordination model • Encapsulated messaging • High-level message protocols Client Server Function(Parameters) Return(Parameters) Agents Blackboard Message Reply

  5. Basics • MAS researchers develop communications languages, interaction protocols, and agent architectures that facilitate the development of multi-agent systems. • MAS researcher can tell you how to program each ant in a colony in order to get them all to bring food to the nest in the most efficient manner, or how to set up rules so that a group of selfish agents will work together to accomplish a given task. • MAS researchers draw on ideas from many disciplines outside of AI, including biology, sociology, economics, organization and management science, complex systems, and philosophy.

  6. Basics • Key elements to achieve multi-agent interaction • a coordination mechanism supported by a common agent communication language and protocol • acollaboration mechanism supported by agent community architecture (including agent and interaction architecture) to support the organization goal • a shared ontology

  7. MAS Architectures (Standards?) • Object Manager Group (OMG) • Foundation for Intelligent Physical Agents (FIPA) • Knowledgeable Agent-oriented System (KAoS) • Open Agent Architecture (OAA) • General Magic group • seems to be out of date...

  8. MAS Architectures • OMG’s Model • Composed of agents and agencies that collaborate using general patterns and policies • Agents are characterized by: • capabilities, type of interaction and mobility • Agencies support: • concurrent execution of agents • security • agent mobility • ...

  9. MAS Architectures • FIPA’s Model • Agents • Agent Platform (AP) • Directory Facilitator (DF) • Agent Management System (AMS) • Agent Communication Channel (ACC) • Agent Communication Language (ACL)

  10. MAS Architectures • KAoS’s Model • An Open Distributed Architecture for Software agents • Defines various agent implementations • Uses conversation policies to elaborate on agent-to-agent communication

  11. MAS Architectures • OAA Model

  12. MAS Architectures • General Magic’s Model • A commercial agent technology for electronic commerce • Views MAS as an electronic marketplace • The marketplace is modeled as a network of computers supporting a collection of places that offer services to mobile agents. • The mobile agents: • can travel, meet other agents, create connections to other places • they have authority.

  13. MAS Architectures • Zeus: a MAS development toolkit

  14. MAS Architectures • Zeus: a MAS development toolkit

  15. MAS Architectures • Geo-Agents (GIS agents) Architecture as a MAS example Other Agent Systems User Task(GeoScript) Reply Query agent Geo-Agents Administrator UI Agent Query agent Exchange registry Pass task Reply Query agent Facilitator Query agent Coordinate Coordinate Task Agent Domain (Service) Agent Control/Reply Domain (Service)Agent Task Agent Retrieve Collaborate Collaborate Data sources

  16. Coordination • Coordination: a process to managedependencies among activities • Common dependencies among activities • State • Shared resource • Producer/Consumer • Prerequisite • Transfer • Usability • Simultaneity constraint • Task/Sub-Task • Worth

  17. Coordination • Three aspects on coordination • Activity aspect • What activity to execute? • When an activity should be executed? • Model to coordinate distributed tasks: Statecharts, Flowcharts, Process algebra, Lotos, SDL, Estelle …

  18. Coordination • Conversation (state) aspect • What is the structure of the conversation among the coordinating entities? • FSM, Petri-Nets, State Transition Diagrams • Implementation aspect • How to implementdistributed software systems where software components coordinate their actions.

  19. Coordination - KQML • Knowledge Query and Manipulation Language (KQML) is both a message format and a message-handling protocol to support run-time knowledge sharing among agents. • KQML comprise a substrate on which to develop higher-level models of inter-agent interaction such as contract nets. • KQML is a coordination mechanism from the conversation aspect

  20. Coordination - KQML • KQML contains an extensible set of performatives, which defines the permissible speech acts agents may use • Example performative: (ask-all /* message layer */ :content "price(IBM, [?price, ?time])“ /* content layer */ :receiver stock-server /* communication layer */ :language standard_prolog :ontology NYSE-TICKS :sender me)

  21. Coordination - KQML

  22. Coordination - KQML • Types of performatives • Basic informative performatives: tell, deny, … • Database performatives: insert, delete, … • Basic responses: error, sorry, … • Basic query performatives: ask-one, ask-all, evaluate,… • Multi-response query performatives: stream-all, … • Basic effector performatives: achieve, …

  23. Coordination - KQML • Types of performatives(Cont.) • Generator performatives: standby, ready, next, … • Capability-definition performatives: advertise • Notification performatives: subscribe • Networking performatives: register, forward, pipe, broadcast, … • Facilitation performatives: broker-one (all), recommend-one (all), recruit-one (all)

  24. Collaboration • Collaboration refers to cooperative effort among agents to reach a single goalby exchanging knowledge built upon the underlying coordination mechanism • Example mechanism: Contract Net Protocol (CNP) • Negotiation as a collaboration mechanism • Negotiation on how tasks should be shared • A task (plan) may be decomposed in a hierarchy of subtasks (hierarchical planning) • An agent may subcontract another agent to perform a (sub)task.

  25. agent agent Bid Contract Task announcement Collaboration - CNP

  26. Collaboration - CNP Phase 1: Task Announcement - The contractor agent publicly announces a task. - Potential candidates evaluate the task according to their won skills and availability. Phase 2: Submission of Bids / Proposals - Agents that satisfy the requiremenst, i.e., are able to perform the task, send their bid / proposal to the contractor.

  27. Collaboration - CNP Phase 3: Selection - The selection of the best candidate is made by the contractor based on received bids and on the CVs of the candidates. • Phase 4: Contract awarding • A contract is established between the contractor and the selected candidate. • - A privileged bilateral communication channel is established between the two agents.

  28. Development of MAS • Define the organization of the MAS according to the problem specification (or solution structure) • Decide the coordination mechanism • Select a MAS implementation framework, e.g., Zeus, that supports the coordination mechanism • Implement the collaborative mechanism which support the MAS organization • Implement shared ontology • Implement each task agent (including customizing associated communication module) • Customize middle agents • Facilitators • Mediators • Brokers • Matchmakers and yellow pages • Blackboards

  29. Applications • Advanced Manufacturing Management Systems • Agents as representatives of machines, users, business processes, etc. • Intelligent Information Search on Internet • Some agents may show learning capabilities (learn the preferences of their users, ..) • Intelligent security enforcement on Internet • Agents are representative of sensors or IDSs • Shopping Agents in Electronic Commerce • With search, price comparison, and bargaining capabilities

  30. Applications • Multi-agent auction in E-commerce • Distributed Surveillance • For information search or to look for special events informing their users of relevant news • Distributed Signal Processing • For problem diagnosis, situation assessment, etc. in the network • Distributed Problem Solving • Collaborative design, scheduling, and planning

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