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Motivation-Based Selection of Negotiation Opponents Steve Munroe and Michael Luck IAM Group University of Southampton.

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Presentation on theme: "Motivation-Based Selection of Negotiation Opponents Steve Munroe and Michael Luck IAM Group University of Southampton."— Presentation transcript:

1 Motivation-Based Selection of Negotiation Opponents Steve Munroe and Michael Luck IAM Group University of Southampton

2 Presentation Outline  The problem: dynamic domains and negotiation  Motivated agents for dynamic domains  Negotiation goals  Selecting opponents

3 Autonomous Negotiation  Three phases of negotiation  Dealing with dynamics and uncertainty  Strategies / Tactics / Protocols  Agent driven  Pre-negotiation: Where do the issues come from? How are reservation values determined? Who best to negotiate with?

4 Autonomy and Motivation Autonomy: The ability to make decisions and select courses of action that further one’s own interests based on one’s own assessment of the situation Motivation: Any desire or preference that can lead to the generation and adoption of goals and that affects the outcome of the reasoning or behavioural task intended to satisfy those goals Motivation >>>> Utility

5 A Motivated Agent Architecture  Motivational Cues  Intensity  Mitigation

6 The Warehouse Domain  Controller agent must negotiate with delivery agent about moving boxes around the warehouse

7 Negotiation Goals  Dynamic reconfiguration of issues to meet current demands Fixed attributes Potential attribute

8 Negotiation Goals - 2  Two types of potential attributes Non resource-based Resource-based

9 Non Resource-Based Attributes: constructing preferences  What is the structure of the preference?  Determined by assessing each possibility in terms of motivational worth

10 Non Resource-Based Attributes: generating preferences  Calculates the worth of each of the possible values that can be used to instantiate a potential attribute : v x gs x ms [0,1]

11 Non Resource-Based Attributes: attribute classification rules  Fixed if the preferences of the agent contains at most one value that has positive motivational worth and all the rest have negative motivational worth.  Negotiable if the preferences of the agent contains more than one value that has positive motivational worth.  Slack if all the values contained in the agent’s preferences have the same motivational worth (both positive or negative).

12 Non Resource-Based Attributes: example preferences

13 Resource-Based Attributes: dynamic constraints  Dynamic evaluation of resource use  Never slack!  Preference structure is monotonic  Problem is to determine reservation on the use of a resource

14 Resource-Based Attributes: the reservation manager  Calculate the unit worth of a resource, r, for an agent, a, UW a r =  r ·bw a r where  r = I m r  [-1,1]  Then obtain the quantity of resource whose (negative) worth is equal to the worth of the goal.

15 Negotiation Goal Structure  A negotiation goal contains sets of Fixed attributes Negotiable attributes Slack attributes Reservation values for resource- dependent attributes

16 Opponent Selection  Selecting to minimise conflict  Selecting to optimise resource use

17 Selecting to Minimise Conflict  Each agent selects its own negotiable attributes  Intersection of choices defines issues  Smaller intersections means less conflict (easier negotiation)

18 The Conflict Minimisation Selection Mechanism  Issue analyser calculates the expected intersection size of this agent’s issues and opponent’s issues  Uses attribute selection frequency information about the opponent

19 Selecting To Optimise Resource Use  Resource manager determines the expected deal price of an opponent  Checks to see if the expected deal price is below reservation  Price profiles  Concessionary flexibility

20 Combining the Mechanisms  Selection based on both conflict minimisation and resource optimisation  Motivationally weighted by the worth of the goal and the worth of the resource

21 Preliminary Evaluation  Tested only on price minimisation  Compare opponent selection against optimal selection  Agent learns to select the optimal

22 Conclusions  Little autonomy apparent in pre-negotiation stage  Motivation enables autonomous decision- making in dynamic negotiation settings  New model of negotiation goals gives scope for motivation-based dynamic decision- making  Characteristics of negotiation goal guides opponent selection.

23 End of Presentation… Questions?


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