multi party multi issue multi strategy negotiation for multi modal virtual agents
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Multi-party, Multi-issue, Multi-strategy Negotiation for Multi-modal Virtual Agents. S antosh S ugur 10/25/2011. Dr. David R Traum. Research Assistant Professor, USC Institute for Creative Technologies, USC. PhD CS , U Rochester Natural Language Processing. Stacy Marsella.

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multi party multi issue multi strategy negotiation for multi modal virtual agents

Multi-party, Multi-issue, Multi-strategy Negotiation for Multi-modal Virtual Agents

Santosh Sugur

10/25/2011

slide2

Dr. David R Traum

  • Research Assistant Professor, USC
  • Institute for Creative Technologies, USC.
  • PhD CS , U Rochester
  • Natural Language Processing.
slide3

Stacy Marsella

  • Research Associate Professor Computer Science, USC
  • Co-Director USC Emotion Group
  • Associate Director, Institute for Creative Technologies – Social Simulation
  • B.A. in Economics from Harvard University
  • Ph.D. in Computer Science from Rutgers University. Focus on AI planning, human problem solving and cognitive science
slide4

Jonathan Gratch

  • Research Associate Professor, USC
  • Associate Director, Institute for Creative Technologies - Virtual Human Research
  • Co-Director, USC Computational Emotion Group
  • Ph.D. in Computer Science, University of Illinois, June 1995
  • Joined ICT in August 1995
slide5

Jina Lee

  • Phd Student under Prof. Stacy Marsella

Arno Hartholt

  • Project leader of the Integrated Virtual Humans group and Central ICT Art Group.
  • BS, MS, University of Twente, Netherlands
  • Joined ICT in 2005
negotiations never cut what you can untie
Negotiations“Never cut what you can untie”
  • Using agents to train humans in negotiations
  • Communicate over multiple modalities – speech, gestures, body postures
  • Dynamic negotiations – change positions and strategies to achieve those goals.
how can a human trainee do well
How can a human trainee do well?
  • Solve problems
  • Gain Trust
    • Familiarity
    • Credibility
    • Solidarity
  • Manage Interactions
multi party dialogue model
Multi-party Dialogue model
  • Maintain a snapshot of Dialogue State – called Information State.
  • Information state is updated by dialogue moves based on certain update rules.
  • Information state and dialogue moves are partitioned into layers each dealing with slightly different aspects.
layers in the dialogue model
Layers in the dialogue model
  • The contact layer concerns whether and how other individuals can be accessible for communication. Modalities include visual, voice (shout, normal, whisper), and radio.
  • The attention layer concerns the object or process that agents attend to. Contact is a prerequisite for attention.
  • The Conversation layer models the separate dialogue episodes that go on during an interaction.
layers in the dialogue model contd
Layers in the dialogue model contd.
  • The participants may be active speakers, addressees, or over hearers.
  • The turn indicates the (active) participant with the right to communicate
  • The initiative indicates the participant who is controlling the direction of the conversation
  • The grounding component of a conversation tracks how information is added to the common ground of the participants.
additions to dialogue model
Additions to dialogue model
  • Listening (input)
    • Improved Gaze model
    • Increase in non verbal feed back during listening.
  • Talking (output)
    • Verbal and non verbal behavior also takes into account where the negotiator’s views are coming from / larger understanding of the issue – helps in negotiation decisions.
    • Dynamically update motivations for strategies based on where the negotiations are at.
multi party n egotiation strategies
Multi Party Negotiation Strategies
    • Apart from disagreements on topics, people may simply dislike each other which is not considered.
  • Find Issue
  • Avoid
  • Attack
  • Negotiate
  • Advocate
  • Success
  • Failure
factors involved in strategy selection
Factors involved in strategy selection
  • Topic
    • is there a topic? – no - find issue()
    • Is it what I want? – no - avoid()
    • Can I work with topic? Yes – negotiate()
  • Control
    • Can I control the discussion
    • I need to control if I have to avoid the topic
  • Utility
    • High utility? Advocate()
    • Absolute utility of issue
    • Relative utility compared to other options
factors involved in strategy selection1
Factors involved in strategy selection
  • Potential
    • How good or bad can the utility get, should I attack or negotiate
  • Trust
    • Do I trust the other interlocutors
  • Commitments
    • Positive commitments are a required for a success strategy
    • Negative commitments result in failure
multi issue utilities
Multi-issue Utilities
  • Agent actions (dialogues) cause agents to achieve their goals.
  • Agents are aware of the goals of other agents
  • Also aware of actions that can achieve or thwart those goals.
  • In negotiations try to weigh different action roadmaps to achieving goals.
  • Choose a plan (roadmap) based on positive utility and the probability that the plan will be executed.
  • Don’t choose a plan if it has negative utility and flaws that will block its execution
expected and potential benefit
Expected and Potential Benefit
  • Expected benefit is a calculation based on commitments and trust.
  • Potential Benefit is the benefit assuming that the plan will succeed.
  • A plan with high potential benefits help to negotiate by advocating that course of action.
different possible actions for a chosen strategy
Different possible actions for a chosen strategy
  • Find Issue
    • Propose a topic
    • Request a topic
    • Initiative parameter dictated which action to take
  • Avoid strategy
    • Change topic to high utility
    • Talk about non-issues
    • Disengage from meeting if there is some control
different possible actions for a chosen strategy1
Different possible actions for a chosen strategy
  • Attack strategy
    • Ad hominem attack
    • Point out flaws in issue
  • Negotiate
    • Attack
    • Propose solutions
  • Advocate
    • Talk about high utility outcomes
    • Address flaws
    • Offer / solicit commitments
discussion points
Discussion points
  • What could be some of the things that could be used in a human to human negotiation, that cannot be used with virtual agents.
    • Eg. Making a connection based on similar past experiences between interlocutors and using that to your advantage.
  • Can such a training setup replace real negotiation experiences?
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