AI Models of Negotiation For the Social Sciences: What Should Be in an AI-and-Law Model of Negotiation? Ronald P. Loui Computer Science and Engineering

AI Models of Negotiation For the Social Sciences:

What Should Be in an AI-and-Law Model of Negotiation?

Ronald P. Loui Computer Science and Engineering / Legal

Studies Washington University in St. Louis

USA

December 06 JURIX 2006 KeyNote 2 Loui

Life's To-Do List…Lecture at the Sorbonne in French…

…Become a President Obama appointee

(was Obama really at ICAIL 2001?)…


What There Is in AI and Law on Negotiation:

AI techniques for modelling legal negotiation -E Bellucci, J Zeleznikow - … ICAIL, 1999Family_Winner: integrating game theory and heuristics to provide negotiation supportJ Zeleznikow, E Bellucci - JURIX, 2003…ODR Environment: Dialogue Tools and Negotiation Support Systems …AR Lodder, J Zeleznikow - Harvard Negotiation Law Review, 2005Integrating Artificial Intelligence, Argumentation and Game Theory to Develop an Online Dispute … E Bellucci, AR Lodder, J Zeleznikow - Tools with Artificial Intelligence, 2004. ICTAI 2004.A framework for group decision support systems: Combining AI tools and OR techniques NI Karacapilidis, CP Pappis - European Journal of Operational Research, 1997Mediation SystemsT Gordon, O Märker - Online-Mediation, 2002A simple scheme to structure and process the information of parties in online forms of alternative ODR GAW Vreeswijk - Proceedings of the First International ODR Workshop (2003) Model Checking Contractual ProtocolsA Daskalopulu - Arxiv preprint cs.SE/0106009, 2001


Where I Start:


Where I Start:

SocSci 174. International Problem Solving. Roger Fisher (Law School). My first freshman lecture at Harvard, first A, …Tutorial: The Russian Army will get bogged down in AfghanistanTerm Paper: The Pershing II's should be deployed in Europe


Principled NegotiationAppeals

To reason or precedentNot merely to position of power



To reason or precedentPERSUADER, Sycara 89, Parsons-Jennings 96Persuasive argumentation in negotiationKP Sycara - Theory and Decision, 1990Collaborative plans for complex group actionBJ Grosz, S Kraus - Artificial Intelligence, 1996Negotiation through argumentation—a preliminary reportS Parsons, NR Jennings - ICMAS, 1996 Arguments, dialogue, and negotiationL Amgoud, S Parsons, N Maudet - ECAI, 2000Argument-based negotiation among BDI agentsSV Rueda, AJ Garcıa, GR Simari - Journal of Computer Science and Technology, 2002



To reason or precedentPERSUADER, Sycara 89, Parsons-Jennings 96Persuasive argumentation in negotiationKP Sycara - Theory and Decision, 1990

Arguing about plans: Plan representation and reasoning for mixed-initiative planningG Ferguson, J Allen - AIPS, 1994Collaborative plans for complex group action BJ Grosz, S Kraus - Artificial Intelligence, 1996Negotiation through argumentation—a preliminary reportS Parsons, NR Jennings – ICMAS, 1996 Arguments, dialogue, and negotiationL Amgoud, S Parsons, N Maudet - ECAI 2000Argument-based negotiation among BDI agentsSV Rueda, AJ Garcıa, GR Simari - Journal of Computer Science and Technology, 2002



To reason or precedentPERSUADER, Sycara 89, Parsons-Jennings 96Persuasive argumentation in negotiationKP Sycara - Theory and Decision, 1990

Understanding the Role of Negotiation in Distributed Search Among Heterogeneous Agents SE Lander, VR Lesser - IJCAI, 1993Collaborative plans for complex group action BJ Grosz, S Kraus - Artificial Intelligence, 1996Negotiation through argumentation—a preliminary reportS Parsons, NR Jennings - ICMAS, 1996 Arguments, dialogue, and negotiationL Amgoud, S Parsons, N Maudet - ICMAS, 2000Argument-based negotiation among BDI agentsSV Rueda, AJ Garcıa, GR Simari - Journal of Computer Science and Technology, 2002



To reason or precedentNot To position of power


Un-Principled NegotiationAppeals

Not To reason or precedentTo position of power



To position of powerEnforceable agreementsUnenforceable agreements

No institutional contextGame Theoretical Models of Negotiation

x Solution Conceptx Nash Equilibriax MultiAgent

Ecommerce Systems




No institutional contextGame Theoretical Models of Negotiationx Solution Conceptx Nash Equilibria - A Beautiful Mind, shared Nobel Prizex MultiAgent Ecommerce Systems - Computers & Thought Winner 03




No institutional contextGame Theoretical Models of Negotiation

x Solution Conceptx Nash Equilibriax MultiAgent

Ecommerce Systems

Badly mistaken path



To position of powerEnforceable agreements

Newer "Institutional Economics" Nobel prizes

Unenforceable agreementsNo institutional context

Game Theoretical Models of Negotiationx Solution Conceptx Nash Equilibriax MultiAgent

Ecommerce Systems


AI Model of Negotiation:Venk Reddy (Harvard) 93, Mark Foltz (WU/MIT),

95Kay Hashimoto (Harvard), 96

Diana Moore's (WU) B.Sc. Thesis, 95-97Anne Jump (Harvard), 97-98

All undergradsBut whom would you have model a social phenomenon?

People who who have VERY good social skillsOR

Someone who thinks human interaction is like playing chess (von Neumann)


AI Model of Negotiation:Diana Moore's B.Sc. Thesis,

Dialogue and Deliberation, 97

Agents that reason and negotiate by arguingS Parsons, C Sierra, N Jennings - Journal of Logic and Computation, 1998Cited by 328


AI Model of Negotiation:Diana Moore's B.Sc. Thesis, 97

SearchDialogue/ProtocolPersuasion/ArgumentationLog-rolling/Problem ReformulationProcess



SearchMixed-initiative planning/NLP-PragmaticsHeuristic valuation of payoffs

Dialogue/ProtocolThis AI and Law community

Persuasion/ArgumentationMultiagent systems community

Log-rolling/Problem ReformulationMixed-initiative planning/NLP-Pragmatics

ProcessToday's Talk


AI-and-Law Model of Negotiation

Offer/acceptance at the level ofScenariosPhrasesTerms

Uncertainty as to How claims might fare if pressedWhether the scenario might occurHow the language might evolveHow the case law (or standards) might evolve



BATNA/security expressed as a RISK positionStrong norms for

ProgressExplanation/ Questions and Answers

Start with utility-payoffs To connect with social scientistsTo be precise & compactI already have a few stories to tell here


Pessimism-Punishment (PP) Agents

Observation: parties to a negotiation (can) construct a probability distribution over potential settlements



Breakdown (BATNA)


Breakdown (BATNA)



Party 1'saspirationParty 2's

aspiration


Party 2'sproposals at t

Party 1'sproposals at t


inadmissible(dominated)at t

inadmissible(dominated)at t


In black:admissiblesettlementsat t

(probabilityof agreementIs non-zero)


Breakdown row

Breakdown column


Breakdownwould occurhere (BATNA)


1's securitylevel

2's securitylevel

2 would rather breakdown

1 would rather breakdown


Eu1|s = 51

Eu2|s = 49α +54(1-α)

Prob(bd) = ?



Observation: parties to a negotiation (can) construct a probability distribution over potential settlementsObservation: from a probability distribution over potential settlements, there is an expected utility given settlementObservation: there is a probability of breakdown p(bd)



Observation: from a probability distribution (at t) over potential settlements, there is an expected utility given settlement (at t)

Observation: there is a probability of breakdown pt(bd)



Definition: At t, calculate

1. An expected utility given settlement (Eut|s) and

2. An expected utility given continued negotiation, Eut = (Eut |s) (1 - pt(bd)) + u(bd) pt(bd)

Definition: Rationality requires the agent, at t, to:

1. Extend an offer, o, if Eut < u(o)

2. Accept an offer, a, if Eut < u(a), a offers-to-you(t)

3. Break down unilaterally if Eut < u(bd)



Pessimism

Empirical Observation: At sufficient granularity, p(bd) is decreasing in the time since last progress


Pessimism causes Eu to fall

Next offer is made at this time

Expectation starts to fall again


Agreement reached as Eu < u1


reciprocated offers

offers


security

Best offer received

Whenever u(acc) > security, acceptance occurs before breakdown!


security

Best offer received

Would you accept an 11-cent offer if yoursecurity were 10-cents?



Observation: You wouldn't accept 11¢ over 10 ¢ security, nor 51 ¢ over 50 ¢ securityObservation: You wouldn't let your kid do itObservation: Your Mother wouldn't let you do itObservation: Your lawyer wouldn't let you do itObservation: Your accountant wouldn't let you do it

Proposition: We shouldn't automate our agents to do it



Question: Isn't this an issue of distributive justiceAnswer: Substantive fairness is trivial to model by transforming utilities

Observation: There may (ALSO) be a procedural fairness issue



Procedural fairness: the more the other party withholds progress, the more you will punish

When the other party resumes cooperation, you are willing to forgo punishment



Resentment

u(bd) = security + resentment(t)

What is resentment? 1. Dignity2. Pride3. Investment in society4. Protection against non-progressive manipulators5. A GENUINE source of satisfaction:

non-material, transactional, personal(?), transitory(?)



Resentment

ut(bd) = security + resentment(t) = u(bd) + r(t)

for NP(t), non-progress for a period t

What is resentment? 6. Attached to a speech/dialogue act:

BATNA through breaking down vs. BATNA through agreement

7. A nonstandard utility (process utility)8. Specific or indifferent (I-bd-you vs. you-bd-me)


Eu never falls to u1


Actually accepts becauseresentment resets with progress

Resentment resets to zero each time there is progress

Nontrivial progess


Resentment might not reset to zero if there is memory

Agent breaks down before accepting


low-valued ρ high-valued ρ

(Assumes no progress)

Linear pess/linear specific pun




Linear pess/linear indifferent pun




Exponential pess/linear indifferent pun


rare alternation betweenbreakdown and acceptance


Exponential pess/sigmoidal specific pun



Variety of Plausible BehaviorsAgent can make a series of offers, responds to offersAgent can wait, then offer, accept, or break downAgent can accept, offer, or break down immediatelyAgent can offer before accepting and vice versaAgent can breakdown before accepting and vice versaAgent can offer before breaking down and vice versaAgent can be on path to breakdown, then on path to acceptance

because received offer changes Eu or resentmentbecause extended offer changes Eu

Concessions in time can be motivatedLaissez-faire paths can be steered


Dominatedby BATNA

1's offers inthis round

2's offer inthis roundEu2

2's aspiration

BATNA =<u1(bd),u2(bd)>

1's aspiration Eu1

What happens when two P&P agents interact?



Eu2

Eu1(t=2)Eu1(t=1)



1'ssecurity+resentment

2'ssecurity+resentment

1's offersin this round







1 breaks down

Amount of(specific)resentment

Laissez-faire path is

<Eu1,Eu2>through time


Does the starting offer affect the laissez-faire path?

Both aregenerousat the start

1 isgenerousat start,2 is not

2 isgenerousat start,1 is not


Breakdownat t=2(purepessimism)


Differentlaissez-fairepaths


Breakdownat t=5withresentment


All paths lead to breakdown


In a different negotiation,some paths lead to acceptance, some to breakdown

Fixedagentcharacteristics

Variedaccelerationof offers


A third example where player 1 can guaranteean acceptance outcome with the right initial offers


An Envelope of NormalcyCan you keep the pathin a narrow envelope?

the axis passes through< uA(bd), uB(bd) >

If so, then agreement isPossible.


Where are the laissez-faire states, in terms of agents' relative power?

power = (ut(bd) – u1)/(Eut – u1)

When any partydoes not have power,Negotiation ends




An AI model of negotiationProcessEnforcement of agreementProcedural fairness / Negotiating normsNonstandard utility attached to speech actObjective probabilityConstructivism (rationality is if, not iff)Purely probabilistic dynamics



An AI model of negotiationProcessEnforcement of agreementProcedural fairness / Negotiating normsNonstandard utility attached to speech actObjective probabilityConstructivism (rationality is if, not iff)Purely probabilistic dynamics



An AI model of negotiationImplementable / Plausible / Simple / MemorableIconoclast (but better)

un-Nashnon-vonNeumannanti-GameTheory

Luce/Raiffa simplicity but requires some modern ideasBrings one main Legal Idea (procedural fairness) into familiar economic settingVictor Lesser: computational value of emotion



An AI model of negotiationImplementable / Plausible / Simple / MemorableIconoclast (but better)

un-Nashnon-vonNeumannanti-GameTheory

Luce/Raiffa simplicity but requires some modern ideasBrings one main Legal Idea (procedural fairness) into familiar economic settingVictor Lesser: computational value of emotion




SearchAnother beautiful story:

how making a proposal in a negotiation dialogue focuses heuristic search which causes utility estimates to build in the more probable settlement areas

Dialogue/ProtocolPersuasion/ArgumentationLog-rolling/Problem ReformulationProcess



SearchDialogue/Protocol

Another beautiful story:How agents can ask each other "WHY NOT?" questions and respond with the specific constraints that cause their objective functions to fall below aspiration

Persuasion/ArgumentationLog-rolling/Problem ReformulationProcess



What beautiful stories will we soon be able to tell here?


What Is At Stake? A Personal View

Intellectual HistoryAI (w/AI and Law) will rewrite the mathematical foundations of the social sciences

Actual Negotiation PracticeWhat electronic world do you want to live in?Can agreement be found in the Middle East?

Documents

AI Models of Negotiation For the Social Sciences: What Should Be in an AI-and-Law Model of Negotiation? Ronald P. Loui Computer Science and Engineering