Design of MultiAgent Systems

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Design of Multi-Agent Systems

• Teacher
• Bart Verheij
• Student assistants
• Albert Hankel
• Elske van der Vaart
• Web site
• http//www.ai.rug.nl/verheij/teaching/dmas/
• (Nestor contains a link)

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Overview

• Introduction
• Task sharing
• The Contract Net
• Result sharing
• Blackboard systems
• Subscribe/notify
• Handling inconsistency
• Coordination
• Partial global planning
• Joint intentions
• Mutual modelling
• Norms and social laws

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Working Together

• Why and how do agents work together?
• Important to make a distinction between
• benevolent agents
• self-interested agents

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Benevolent Agents

• If we own the whole system, we can design
  agents to help each other whenever asked
• In this case, we can assume agents are
  benevolent our best interest is their best
  interest
• Problem-solving in benevolent systems is
  cooperative distributed problem solving (CDPS)
• Benevolence simplifies the system design task
  enormously

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Self-Interested Agents

• If agents represent individuals or organizations,
  (the more general case), then we cannot make the
  benevolence assumption
• Agents will be assumed to act to further their
  own interests, possibly at expense of others
• Potential for conflict
• May complicate the design task enormously

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Task Sharing and Result Sharing

• Two main modes of cooperative problem solving
• task sharingcomponents of a task are
  distributed to component agents
• result sharinginformation (partial results,
  etc.) is distributed

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Overview

• Introduction
• Task sharing
• The Contract Net
• Result sharing
• Blackboard systems
• Subscribe/notify
• Handling inconsistency
• Coordination
• Partial global planning
• Joint intentions
• Mutual modelling
• Norms and social laws

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The Contract Net

• A well known task-sharing protocol for task
  allocation is the Contract Net
• Recognition
• Announcement
• Bidding
• Awarding
• Expediting

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The Contract Net
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Recognition

• In this stage, an agent recognizes it has a
  problem it wants help with.
• Agent has a goal, and either
• realizes it cannot achieve the goal in isolation
  does not have capability
• realizes it would prefer not to achieve the goal
  in isolation (typically because of solution
  quality, deadline, etc.)

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Announcement

• In this stage, the agent with the task sends out
  an announcement of the task which includes a
  specification of the task to be achieved
• Specification must encode
• description of task itself (maybe executable)
• any constraints (e.g., deadlines, quality
  constraints)
• meta-task information (e.g., bids must be
  submitted by)
• The announcement is then broadcast

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Bidding

• Agents that receive the announcement decide for
  themselves whether they wish to bid for the task
• Factors
• agent must decide whether it is capable of
  expediting task
• agent must determine quality constraints price
  information (if relevant)
• If they do choose to bid, then they submit a
  tender

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Awarding Expediting

• Agent that sent task announcement must choose
  between bids decide who to award the contract
  to
• The result of this process is communicated to
  agents that submitted a bid
• The successful contractor then expedites the task
• May involve generating further manager-contractor
  relationships sub-contracting

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Issues for Implementing Contract Net

• How to
• specify tasks?
• specify quality of service?
• select between competing offers?
• differentiate between offers based on multiple
  criteria?

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Overview

• Introduction
• Task sharing
• The Contract Net
• Result sharing
• Blackboard systems
• Subscribe/notify
• Handling inconsistency
• Coordination
• Partial global planning
• Joint intentions
• Mutual modelling
• Norms and social laws

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Result Sharing in Blackboard Systems

• The first scheme for cooperative problem solving
  the blackboard system
• Results shared via shared data structure (the
  blackboard)
• Multiple agents can read and write to the
  blackboard
• Agents write partial solutions to the blackboard
• The blackboard may be structured into hierarchy
• Mutual exclusion over the blackboard required ?
  bottleneck
• Not concurrent activity

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Result Sharing in Subscribe/Notify Pattern

• Common design pattern in object-oriented systems
  subscribe/notify
• An object subscribes to another object, saying
  tell me when event e happens
• When event e happens, original object is notified
• Information pro-actively shared between objects
• Objects required to know about the interests of
  other objects ? inform objects when relevant
  information arises

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Overview

• Introduction
• Task sharing
• The Contract Net
• Result sharing
• Blackboard systems
• Subscribe/notify
• Handling inconsistency
• Coordination
• Partial global planning
• Joint intentions
• Mutual modelling
• Norms and social laws

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Handling inconsistency

• Inconsistencies about
• Beliefs
• Goals/intentions
• Inevitable except in small systems
• Approaches
• Do not allow or ignore
• Resolve by negotiation
• Design for graceful degradation (best choice)

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Handling inconsistency

• A design for graceful degradation
• Functionally Accurate/ Cooperative (FA/C)
  Systems (Lesser and Corkill)
• A network problem solving structure
• Functionally accurate the generation of
  acceptably accurate solutions without the
  requirement that all shared intermediate results
  be correct and consistent
• Cooperative an iterative, coroutine style of
  node interaction in the network

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Handling inconsistency

• Characteristics of FA/C systems
• Problem solving not in a strict predetermined
  order, but opportunistically
• Communication of high-level data, not raw data
• Solve inconsistency implicitly by exchanging
  partial results, not at beginning or end
• - There exist multiple solution routes

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Overview

• Introduction
• Task sharing
• The Contract Net
• Result sharing
• Blackboard systems
• Subscribe/notify
• Handling inconsistency
• Coordination
• Partial global planning
• Joint intentions
• Mutual modelling
• Norms and social laws

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Coordination

• Partial global planning (Durfee)
• Partial no plan for the entire problem
• Global exchange of local plans for non-local
  view
• Stages
• Each agent decides on goals generate short-term
  plans
• Information on interacting plans and goals is
  exchanged
• Each agent alters local plans
• Metalevel dictates information exchange (which
  agents, under which conditions)

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Coordination

• Joint intentions (Levesque et al)
• Coordinated non-cooperative vs. coordinated
  cooperative action
• Going to the same place to find shelter or to
  perform a choreography
• Commitment a promise
• Convention a means for commitment monitoring
• Commitments are assumed to persist Joint
  Persistent Goals
• Agents have a collective commitment to bring
  about some goal and a motivation for the goal.
  Agents inform each other about the status of the
  goal (satisfied/impossible/disappearance of
  motivation)

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Coordination

• Mutual modelling (e.g., Gassers MACE)
• Agent keeps models of itself and other agents,
  e.g., with respect to roles, skills, goals, plans
• Characteristic no explicit communication
  required

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Coordination

• Norms and social laws
• Important in everyday life
• Origin of conventions
• Offline design (straightforward)
• Emergence (scalable, flexible)
• Tee shirt game (Shoham Tennenholtz)
• How to update strategy? (e.g., majority or
  highest cumulative reward)

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Overview

• Introduction
• Task sharing
• The Contract Net
• Result sharing
• Blackboard systems
• Subscribe/notify
• Handling inconsistency
• Coordination
• Partial global planning
• Joint intentions
• Mutual modelling
• Norms and social laws

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Student presentations