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

2. 14 -2 Basics

3. 14 -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. 14 -4 Basics 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 ClientServer Intelligent Agents Intelligent Agents Intelligent Agents Function(Parameters) Return(Parameters) Blackboard Message Reply Traditional Software Agents Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents Intelligent Agents

5. 14 -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. 14 -6 Basics Key elements to achieve multi-agent interaction –a coordination mechanism supported by a common agent communication language and protocol –a collaboration mechanism supported by agent community architecture (including agent and interaction architecture) to support the organization goal –a shared ontology

7. 14 -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Agents (FIPA) Knowledgeable Agent-oriented System (KAoS) Open Agent Architecture (OAA) General Magic group –seems to be out of date...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. 14 -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. 14 -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. 14 -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. 14 -11 MAS Architectures OAA Model

12. 14 -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. 14 -13 Zeus: a MAS development toolkit MAS Architectures

14. 14 -14 MAS Architectures Zeus: a MAS development toolkit

15. 14 -15 Geo-Agents Domain (Service) Agent Task Agent Facilitator AdministratorUI Agent Task Agent Other Agent SystemsUser Query agent Exchange registry Query agent Pass task Reply Coordinate Collaborate Control/Reply Task(GeoScript) Reply Collaborate Data sources Retrieve Geo-Agents (GIS agents) Architecture as a MAS example MAS Architectures

16. 14 -16 Coordination Coordination: a process to manage dependencies among activities Common dependencies among activities –State Shared resource Producer/Consumer –Prerequisite –Transfer –Usability Simultaneity constraint –Task/Sub-Task –Worth

17. 14 -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. 14 -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 implement distributed software systems where software components coordinate their actions.

19. 14 -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. 14 -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. 14 -21 Coordination - KQML

22. 14 -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. 14 -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. 14 -24 Collaboration Collaboration refers to cooperative effort among agents to reach a single goal by 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. Contract Bid agent Collaboration - CNP Task announcement

26. 14 -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. 14 -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. 14 -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. 14 -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. 14 -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