Chapter 16: Multiagent Systems

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• Chapter 16Multiagent Systems

Service-Oriented Computing Semantics, Processes,
Agents Munindar P. Singh and Michael N. Huhns,
Wiley, 2005
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Highlights of this Chapter

• Applicability in Service-Based Systems
• Multiagent Architecture
• Agent Types
• Lifecycle Management
• Consistency Maintenance
• Modeling Other Agents
• Cognitive Concepts

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Basic Problems of MAS

• Distributing control among agents
• Describing, decomposing, distributing tasks
• Interacting and communicating
• Representing goals, problem-solving states, and
  other agents
• Maintaining consistency, reconciling conflicts

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(de facto) Standard Agent Types
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Brokerage Service

• Cooperates with a Directory Service
• An agent requests the Brokerage Service to
  recruit one or more agents who can provide a
  service
• Brokerage Service uses knowledge about the
  requirements and capabilities of registered
  agents to
• Determine the appropriate agents to which to
  forward a request for a service
• Negotiates with the agents to determine a
  suitable set of service providers
• Potentially learn about the properties of the
  responses
• example Brokerage agent determines that
  advertised results from agent X are incomplete
  and seeks a substitute for X

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FIPA Agent Management System
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Agent Management System 2

• Handles the creation, registration, location,
  communication, migration and retirement of
  agents. Provides the following services
• White pages, such as agent location, naming and
  control access services, which are provided by
  the Agent Management System (AMS). Agent names
  are represented by a flexible and extensible
  structure called an agent identifier, which can
  support social names, transport addresses, name
  resolution services, amongst other things
• Yellow pages, such as service location and
  registration services, which are provided by the
  Directory Facilitator (DF)
• Agent message transport services

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Java Agent Development Framework

• JADE, the most popular FIPA-compliant agent
  framework for multiagent systems
• http//jade.tilab.com/
• The most established of the publicly available
  agent frameworks
• (FIPA-OS and Zeus having died)

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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

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Architecture of TMS-Based Agent

• Problem solver decides on actions
• TMS maintains a network of beliefs based on the
  justifications relating them

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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

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Distributed TMS

• Each agent has a justification-based TMS
• Each datum can have status
• OUT
• IN valid local justification
• EXTERNAL must be IN for some agent
• When a problem solver adds or removes a
  justification, the DTMS
• Unlabels data based on the changed justification
• Relabels all unlabeled shared data (in one or
  more iterations)

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Degrees of Logical Consistency

• Inconsistency an agent is individually
  inconsistent
• Local Consistency all agents are individually
  consistent
• Local-and-Shared Consistency agents are locally
  consistent and agree about any data they might
  share
• Global Consistency agents are globally
  consistent (union of KBs is consistent)
• The DTMS maintains local-and-shared consistency
  and well-foundedness

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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
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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)
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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)
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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
--gt OUT r1 recommend(X) - takeover-bid(X)
IN r2 takeover-bid(X) - cash-rich(X) IN f3
recommend(xcorp) IN --gt OUT Shared with
Client Justification (f2 r1 r2)
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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)
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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