Managing Social Influences through Argumentation-Based Negotiation

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Managing Social Influences throughArgumentation-B
ased Negotiation

• Present by Yi Luo

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Paper in workshop of AAMAS-06

• Fifth International Joint Conference on
  AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS (AAMAS
  2006)
• Workshop Argumentation in Multi-Agent Systems
  (ArgMAS)
• Nishan C. Karunatillake1, Nicholas R. Jennings1,
  Iyad Rahwan2, Sarvapali D. Ramchurn1. Managing
  Social Influences through Argumentation-Based
  Negotiation
• School of Electronics and Computer Science,
  University of Southampton, Southampton, UK.
• Institute of Informatics, The British University
  in Dubai
• (Fellow) School of Informatics, University of
  Edinburgh, Edinburgh, UK.

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Background

• internal influences Vs. social influence
• Internal intrinsic motivations
• External role, relationship
• Example a teacher is trying to sell a book to
  his student
• Incomplete knowledge dont know status in
  society
• Conflict between internal and social influence

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Background

• Argumentation-based negotiation (ABN)
• exchange additional meta-information such as
  justifications, critics, and other forms of
  persuasive language
• gain a wider understanding of the internal and
  external influences

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Background

• Objective
• Propose a ABN framework allowing agents detect,
  manage and resolve conflicts
• Giving agents the capability to challenge their
  counter parts and obtain the reasons for
  violating social commitment
• simulate to compare the result for agents with
  and without argumentation in the social context

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Social Argumentation Model

• Social influence schema
• Social Arguments
• language and protocol
• Decision functions

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Social Argumentation Model Social Influence
Schema

• Social commitment
• x debtor y creditor ? action
• Social commitment is a commitment by agent x to
  another agent y to perform a stipulated action ?
• x attains an obligation toward the y to action ?
• y attains certain right to demand (compensation)
  or require the performance of ?
• relationship encapsulation of social commitments
  between associated roles

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Social Argumentation Model Social Influence
Schema

• Act (x, student) and RoleOf(student,
  student-teacher-relationship) In (x, student,
  student-teacher-relationship)

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Social Argumentation Model Social Influence
Schema
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Social Argumentation Model Social Influence
Schema
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Social Argumentation Model Social Influence
Schema

• every two agents combined with an action can be
  associated together as a social commitment
• A set of SCs can be associated together as a
  relationship
• Every two roles in the society can have a
  relationship

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Social Argumentation ModelSocial Arguments

• Socially influencing decision argue about
  validity of reasoning
• Dispute a1 is in role r1, SC is a social
  commitment associated with relationship p
• Rebut agent is also is another role which
  associate another action
• Rebut conflicts between two existing obligations,
  rights and actions
• Negotiating social influence trading
• promise to undertake future obligation
• Promise not to exercise certain right

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Social Argumentation ModelLanguage and Protocol

• Domain language communication language
  Utterance
• Domain language premise about social context
  conflicts that may face while executing actions
• Communication language elocutionary parties
  OPEN-DIALOGUE, PROPOSE, ACCEPT, REJECT,
  CHALLENGE, ASSERT AND CLOSE-DIALOGUE

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Social Argumentation ModelLanguage and Protocol

• Protocol
• Opening
• Conflict recognition initial interaction, bring
  the conflict in surface
• Conflict diagnosis establish root cause of the
  conflict
• Conflict management allows agents to argue
  addressing the cause of this conflict
• Agreement mutually acceptable solution or
  agreeing to disagree
• Closing

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Social Argumentation Model Decision Making
Functionality
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Social Argumentation Model Decision Making
Functionality

• Challenge the rejection / end negotiation /
  forward an alternative proposal
• Generating a proposal
• If it is capable of performing the reward
• If the benefit it gains from the request is
  greater than the cost of reward
• Evaluating a proposal
• if it is capable of performing the request
• The benefit of the reward is greater than the
  cost incerred in performing the request

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Social Argumentation Model Decision Making
Functionality
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Argumentation Context

• Scenario task allocation
• Self-interested agents interact to obtain
  services to achieve a given set of actions
• Agent has
• A list of actions that is required to achieve
• Capability to perform actions

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Argumentation Context Scenario

• Capability type level
• Actions time capability type minimum
  capability level reward

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Argumentation Context modeling Social Influence

• Role-relationship structure
• Associated degree of influence decommitment
  penalty
• Assign roles to actual agents

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Argumentation Context modeling Social Influence
Agent a0 Obligation to provide - c0 to an
agent acting r1 obliged to pay 400 if
decommitted. - c1 to an agent acting r1 obliged
to pay 100 if decommitted. Rights to demand -
c0 from an agent acting r1 right to demand 200
if decommitted.
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Argumentation Context modeling Social Influence

• Test how agents use argumentation to manage and
  resolve conflicts created due to incomplete
  knowledge about their social influence
• Provide only a subset of the agent-role map
• perfect knowledge (0 missing knowledge)
• Completely unaware of social influence (100
  missing knowledge)

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Argumentation Context Agent Interaction

• An agent requires a certain capability will
  generate and forward proposals to another agent,
  asking him to sell its service in exchange for a
  certain reward (algorithm 1) propose (do (aj,
  ?j), do (ai, m))
• If the receiving agent perceives this proposal to
  be viable and believes it is capable of
  performing it, then will accept it. Otherwise it
  will reject the proposal (Algorithm 2).

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Argumentation Context Agent Interaction

• In case of a reject, the original proposing agent
  will attempt to forward a modified proposal. The
  interaction will end either when one of the
  proposals is accepted or when all valid proposals
  that the proposing agent can forward are rejected
  (Algorithm 3).
• agents argue (algorithm 4)
• detect conflicts by analyzing the decommitment
  penalties
• Try to resolve it by exchanging their respective
  justifications
• If there are inconsistencies, social arguments
  are used
• If they are both valid, then each agent would
  point-out alternative justifications via
  asserting missing knowledge
• The defeat-status is computed via a validation
  heuristic, which simulates a defeasible model

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Argumentation Context Agent Interaction
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Managing Social Influences

• Demanding compensation
• Right to demand compensation and the right to
  challenge non-performance of social commitment

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Managing Social Influences
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Managing Social Influences

• Observation 1 The argumentation strategy allows
  agents to manage their social influences even at
  high uncertainty levels.
• Observation 2 In cases of perfect information
  and complete uncertainty, both strategies perform
  equally.
• Observation 3 At all knowledge levels, the
  argumentation strategy exchanges fewer messages
  than the non-arguing one.

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Managing Social Influences
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Managing Social Influences

• Observation 4 When there are more social
  influences within the system, the performance
  benefit of arguing is only significant at high
  levels of knowledge incompleteness.

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Managing Social Influences

• Questioning non-performance
• Argue-In-First-Rejection and Argue-In-Last-Rejecti
  on
• Observation 5 The effectiveness of the various
  argumentation strategies are broadly similar
• Observation 6 Allowing the agents to challenge
  earlier in the dialogue, significantly increases
  the efficiency of managing social influences.

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Managing Social Influences
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Conclusion

• The incomplete knowledge and the diverse
  conflicting influences may prevent agents from
  negotiation
• in order to function as a coherent society,
  agents require a mechanism to manage their social
  influences in a systematic manner.
• Argumentation based approach improve the
  multi-agent system to form an agreement more
  effectively and efficiently.

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Questions?

• Thank you