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Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

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Page 1: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

NegotiationA Lesson in Multiagent System

Based on Jose Vidal’s bookFundamentals of Multiagent Systems

Henry Hexmoor

SIUC

Page 2: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Negotiation: The Bargaining Problem

• Interaction in order to agree on a deal• Approach is to exchange messages among agents

– Objective is to reach a deal, that:

1. maximizes utilities,

2. avoids expiration,

3. avoids risk of conflict, and

4. avoid failure on deal

Page 3: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Automated Negotiation

• Knowledge and Decision making is distributed to local sites• Utilities are optimized without:

1. central aggregation, or

2. central reasoning

Examples:• Large organizations, governments, societies

Page 4: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Bargaining problem(Nash 1950)

Where represents set of deals

R represents real number of states

• : the no deal deal• i.e., agent prefers no deal to

negative utility

Rui :

)(u

Page 5: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Pareto Optimal

• A deal is Pareto Optimal if there is no other deal such that no one prefers it over

Page 6: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

• For two agents i and j

Pareto Frontier

Space of possible deals

A deal

j

i

Page 7: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

• A Negotiation is independent of utility units if when U chooses and when given

chooses

Where

e.g., money in different countries

UuuuuU II :,...,,' 2211 '

)()'( iiii uu

Independence of Utility units Property

Page 8: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Symmetry Property

• A negotiation protocol is symmetric if the solution remains the same as long as the set of utility function U is the same, regardless of which agent has which the utility.

Page 9: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Rationality

• A deal is individually rational iff

)()( iii uu

Page 10: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

• A negotiation to protocol is independent of irrelevant alternatives if it is true that when given the set of possible deals it chooses and when where it again chooses , assuming U stays constant

' '

Irrelevant Alternatives Property

Page 11: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Egalitarian Solution

• Gains are equally shared and

Where E represents set of deals which equal payoff

)'(maxarg'

ii

Eu

)()( ji

ijuuE

Page 12: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Egalitarian solution for two…

Egalitarian deal may not be Pareto Optimal

iu

ju

Page 13: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Egalitarian Social Welfare solution

• A deal that maximizes the utility received by the agent with the smallest utility

Example: Helping the poor!

)(minmaxarg i

iu

Every problem is guaranteed to have an egalitarian social welfare solution

Page 14: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Utilitarian solution

• A deal that the deal that maximizes the sum of all utilities

• The utilitarian deal is a Pareto optimal deal. • There might be more than one utilitarian deals in the case of a tie. • The utilitarian deal violates the independence of utility units assumption.

)(maxarg i

iu

Page 15: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Nash Bargaining solution• A deal that maximizes the product of the utilities :

• The Nash solution is 1. Pareto efficient,

2. independent of utility units,

3. symmetric, and

4. independent of irrelevant alternatives.

)'(maxarg'

iu

Page 16: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Kalai-smorodinsky

• A deal that distributes utilities in proportion to the maximum that the agent can get.

Human preferences for deals is complex!

Page 17: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

The Rubinstein Bargaining Process• Agents act only at discrete time steps. • In each time step, one of the agents proposes a deal to the other

who either accepts it or rejects it. • If the offer is rejected then we move to the next time step where

the other agent gets to propose a deal. • Once a deal has been rejected it is considered void and cannot

be accepted at a later time.• The alternating offers models does not have a dominant

strategy.• We assume that time is valuable. The agents’ utility for all

possible deals is reduced as time passes. E.g., haggling over how to split an ice cream sundae which is slowly melting.

Page 18: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Time matters

• Introducing a discount factor

= i’s discount coefficient at time t

= 0 do it now or lose

= 1 do it whenever . . .• The agents’ utility for every possible deal decreases

monotonically as a function of time with a discount factor.

ti

Page 19: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Theorem

• The Rubinstein alternating offers game where the agents have complementary linear utilities has a unique subgame perfect equilibrium strategy where– Agent i proposes a deal

and accept the offer from j only if– Agent j proposes a deal

and accept the offer from i only if

ji

ji

1

1*

j ),()( *jiji uu

iji

ij

1

1*

)()( *ijij uu

Page 20: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Corollaries

)1(1 **jji

**iij

Page 21: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Monotonic Concession Protocol

2.7

)()'()()'('.6

.5

)()(.4

.3

.2

)(maxarg.1

goto

uuanduuthatsuchelse

acceptthen

uuif

proposalreceive

propose

u

iiiijijij

j

iiji

j

i

ii

Page 22: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Zeuthern strategy

• Willingness to risk deal break down, riski

• Agent calculates the risks for both agents. • The agent with the smallest risk should concede just enough to get

the deal agreed in one step. • Zeuthern strategy converges to Nash solution.

)(

)()(

ii

jiii

u

uu

Page 23: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

One step negotiation (Rosenscheinand Zlotkin, 1994)

ji

ijiijjji

j

i

iE

i

jiji

andbetweenrandomlychoosetojwithcoordinateelse

strategyfollowingnotisjerrorreportthen

uuuuif

receive

propose

u

uuuuE

,.7

,.6

)()()()(.5

.4

.3

)(maxarg.2

)}'()'()()(|{.1 '

• Each agent then has two proposals: the one it makes and the one it receives. • The agents must accept the proposal that maximizes the product of the agents’ utilities. • If there is a tie then they coordinate and choose one of them at random.

Page 24: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Distributed Search

Search through dominant deals as in a hill climbing strategy problems my exist

Deals that dominate 0

Page 25: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Ad-hoc Negotiation Strategies

• Faratin(Jenning’s student) deployed Multiagent Negotiation systems, such as ADEPT

Page 26: Negotiation A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor SIUC

Task allocation problem

mapping

• agent i incurs a cost for performing task S

Example: Postman problem: Trading letters to lower

their costs Problems with lies . . .

AT

RSCi :