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Chapter 16: Multiagent Systems

Chapter 16: Multiagent Systems. Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005. Highlights of this Chapter. Applicability in Service-Based Systems Multiagent Architecture Agent Types Lifecycle Management

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Chapter 16: Multiagent Systems

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  1. Chapter 16:Multiagent Systems Service-Oriented Computing: Semantics, Processes, Agents– Munindar P. Singh and Michael N. Huhns, Wiley, 2005

  2. Highlights of this Chapter • Applicability in Service-Based Systems • Multiagent Architecture • Agent Types • Lifecycle Management • Consistency Maintenance • Modeling Other Agents • Cognitive Concepts Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  3. Basic Problems of MAS • Distributing control among agents • Describing, decomposing, distributing tasks • Either the designer does it • Or the agents negotiate it autonomously • Designing agents to support the above • Interacting and communicating • Negotiating • Special case in cooperative, homogeneous setting: maintaining consistency Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  4. (de facto) Standard Agent TypesDesign-time (static) breakdown of functionality and tasks Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  5. Brokerage ServiceViewed as an Agent Type • Cooperates with a Directory Service • Accepts requests from agents to recruit one or more agents who can provide a service • Uses knowledge about the requirements and capabilities of registered agents to • Identify appropriate agents for an interaction • Negotiate with selected agents • Potentially learn about the properties of the responses • Example: Brokerage determines that advertised results from agent X are incomplete and seeks a substitute for X Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  6. FIPA Agent Management SystemFoundation for Intelligent and Physical Agents (now in IEEE) • Good • Architecture (notions of agents and interaction) • Wrong • Protocol models • Mentalist focus Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  7. Agent Management System: 2Analogous to an JEE Container • Handles the creation, registration, location, communication, migration, and retirement of agents • White pages, e.g., agent location and naming (from AMS) • Agent identifiers support social names, transport addresses, name resolution services • Yellow pages, e.g., service location and registration services (from DF) • Agent message transport services Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  8. Agent Frameworks • JADE, a popular FIPA-compliant agent framework for multiagent systems: • http://jade.tilab.com/ • (FIPA-OS and Zeus having died) Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  9. Consistency Maintenance across Services A truth maintenance system (TMS) helps maintain consistency • Performs a form of propositional deduction • Maintains justifications and explains the results of its deductions • Updates beliefs incrementally when premises change TMSs help us • Deal with atomicity • Maintain modular models Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  10. justifications Problem Solver TMS beliefs Architecture of TMS-Based Agent • Problem solver: decides on actions • TMS: maintains a network of beliefs • Justifications of a belief based on others help make corrections to reasoning Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  11. Knowledge Base Integrity • Stability: believe everything justified validly; disbelieve everything else • Well-Foundedness: no circular beliefs • Logical consistency: no logical contradictions • Completeness: find a consistent state if one exists, or report failure Problems arise when knowledge is distributed Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  12. Distributed TMS • Each agent has a justification-based TMS • Each datum can have status • OUT (not believed) • IN: valid local justification (believed) • EXTERNAL: must be IN for some agent • When a problem solver adds or removes a justification, the DTMS checks if some datum is affected • Unlabels data based on the changed datum • Relabels all unlabeled shared data (in one or more iterations) • Notifies other agents who have an interest in any datum, i.e., those with whom the datum is shared Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  13. Degrees of Logical Consistency • Inconsistency: an agent is internally inconsistent • All bets are off with such an agent • Local Consistency: all agents are individually consistent • Totally disconnected agents can’t interact effectively • Global Consistency: union of KBs is consistent • Total integration is not viable in open settings • [DTMS] Local-and-Shared Consistency: agents are locally consistent and agree about any data they might share • Captures essential interdependence Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  14. Cooperative Service: 1 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN ? recommend(?X) Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) IN r2: recommend(X) :- takeover-bid(X) IN r1: takeover-bid(X) :- cash-rich(X) IN Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  15. Cooperative Service: 2 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN recommend(XCorp) Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) IN r1: recommend(X) :- takeover-bid(X) IN r2: takeover-bid(X) :- cash-rich(X) IN f3: recommend(xcorp) IN Shared with: Client; Justification: (f2 r1 r2) Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  16. Cooperative Service: 3 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN f4: recommend(xcorp) EXTERNAL Shared with: Broker; Justification: ( ) f5: buy(xcorp) IN Justification: (f3 f4 r3) Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) IN r1: recommend(X) :- takeover-bid(X) IN r2: takeover-bid(X) :- cash-rich(X) IN f3: recommend(xcorp) IN Shared with: Client; Justification: (f2 r1 r2) Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  17. Cooperative Service: 4 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN f4: recommend(xcorp) EXTERNAL Shared with: Broker; Justification: ( ) f5: buy(xcorp) IN Justification: (f3 f4 r3) relabel recommend(XCorp) Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) IN --> OUT r1: recommend(X) :- takeover-bid(X) IN r2: takeover-bid(X) :- cash-rich(X) IN f3: recommend(xcorp) IN --> OUT Shared with: Client; Justification: (f2 r1 r2) Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  18. Cooperative Service: 5 Client f3: afford(xcorp) IN r3: buy(X) :- query(Broker recommend(X)), afford(X) IN f4: recommend(xcorp) OUT Shared with: Broker; Justification: ( ) f5: buy(xcorp) OUT Justification: (f3 f4 r3) Broker f1: afford(xcorp) OUT f2: cash-rich(xcorp) OUT r1: recommend(X) :- takeover-bid(X) IN r2: takeover-bid(X) :- cash-rich(X) IN f3: recommend(xcorp) OUT Shared with: Client; Justification: (f2 r1 r2) Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  19. DTMS Scope • Ensures consistent state with respect to shared data • Considers one state of the world • Even though agents may learn or unlearn data about the same state • Not suitable for dealing with a changing world • Cannot deal with real-world actions that an agent cannot undo Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  20. Chapter 16 Summary Study multiagent systems because interactions among agents make them interesting • Communication among agents is key, although markets (later chapter) only support implicit communication through prices • Programming environments support agent interactions • Consistency maintenance is a major challenge • Agents must model agents; simple techniques are often adequate; more subtle techniques can require extensive reasoning power Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

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