A New Model of Negotiation Based on Pessimism and Punishment Ronald P. Loui Washington University St. Louis CAEPIA 2003.

Slides:

Advertisements

Similar presentations

Procedural justice and a constructive approach to negotiating with stakeholders Jill Howieson.

Advertisements

BUSINESS EGGS NEGOTIATION. RELATIONSHIP CONFLICTS Strong Emotions Misperceptions or Stereo types Poor or miscommunication Negative behavior DATA CONFLICTS.

Reaching Agreements II. 2 What utility does a deal give an agent? Given encounter  T 1,T 2  in task domain  T,{1,2},c  We define the utility of a.

This Segment: Computational game theory Lecture 1: Game representations, solution concepts and complexity Tuomas Sandholm Computer Science Department Carnegie.

Tarak Bahadur KC, PhD Negotiation Skills Negotiation Skills Tarak Bahadur KC, PhD

Game Theory and Computer Networks: a useful combination? Christos Samaras, COMNET Group, DUTH.

MIT and James Orlin © Game Theory 2-person 0-sum (or constant sum) game theory 2-person game theory (e.g., prisoner’s dilemma)

 1. Introduction to game theory and its solutions.  2. Relate Cryptography with game theory problem by introducing an example.  3. Open questions and.

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

Online Scheduling with Known Arrival Times Nicholas G Hall (Ohio State University) Marc E Posner (Ohio State University) Chris N Potts (University of Southampton)

Lecture 2A Strategic form games

Argumentation in Artificial Intelligence Henry Prakken Lissabon, Portugal December 11, 2009.

Game Theory The study of rational behavior among interdependent agents Agents have a common interest to make the pie as large as possible, but Agents have.

Chapter 6 © 2006 Thomson Learning/South-Western Game Theory.

EC941 - Game Theory Prof. Francesco Squintani Lecture 8 1.

EC102: Class 9 Christina Ammon.

Reducing Costly Information Acquisition in Auctions Kate Larson, University of Waterloo Presented by David Thompson, University of British Columbia July.

Gabriel Tsang Supervisor: Jian Yang.  Initial Problem  Related Work  Approach  Outcome  Conclusion  Future Work 2.

Lecture 1 - Introduction 1.  Introduction to Game Theory  Basic Game Theory Examples  Strategic Games  More Game Theory Examples  Equilibrium  Mixed.

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.

1 Section 2d Game theory Game theory is a way of thinking about situations where there is interaction between individuals or institutions. The parties.

UNIT II: The Basic Theory Zero-sum Games Nonzero-sum Games Nash Equilibrium: Properties and Problems Bargaining Games Bargaining and Negotiation Review.

Distributed Rational Decision Making Sections By Tibor Moldovan.

Software Agents in Economic Environments Robert S. Gazzale Ph.D. Candidate, Department of Economics Jeffrey MacKie Mason Professor, Dept. of Economics.

Introduction to Game Theory and Behavior Networked Life CIS 112 Spring 2009 Prof. Michael Kearns.

Extensive Game with Imperfect Information Part I: Strategy and Nash equilibrium.

Interest-Based Bargaining

UNIT II: The Basic Theory Zero-sum Games Nonzero-sum Games Nash Equilibrium: Properties and Problems Bargaining Games Bargaining and Negotiation Review.

Recent Research Studies on Cooperative Games In the recent years since around 2003 I have been doing research following up on a specific idea for the finding.

A Study of Computational and Human Strategies in Revelation Games 1 Noam Peled, 2 Kobi Gal, 1 Sarit Kraus 1 Bar-Ilan university, Israel. 2 Ben-Gurion university,

Strategic Game Theory for Managers. Explain What is the Game Theory Explain the Basic Elements of a Game Explain the Importance of Game Theory Explain.

CHAPTER 4 Negotiation : Strategy and Planning

1 Bargaining & Markets u As before: Buyers and Sellers, δtp,δtp, δ t (1-p). u Matching: Seller meets a buyer with probability α. A buyer meets a seller.

Copyright © 2008 Allyn & Bacon Negotiation and Conflict Management 12 CHAPTER Chapter Objectives This Multimedia product and its contents are protected.

MAKING COMPLEX DEClSlONS

Agenda, Day 2  Questions about syllabus? About myths?  Prisoner’s dilemma  Prisoner’s dilemma vs negotiation  Play a single round  Play multiple rounds.

Team Formation between Heterogeneous Actors Arlette van Wissen Virginia Dignum Kobi Gal Bart Kamphorst.

© 2011 Brooks/Cole, A Division of Cengage Learning Chapter 16 Consultation and Collaboration You must be the change you wish to see in the world. Mahatma.

Intermediate Microeconomics

Standard and Extended Form Games A Lesson in Multiagent System Based on Jose Vidal’s book Fundamentals of Multiagent Systems Henry Hexmoor, SIUC.

Linking multi-agent simulation to experiments in economy Re-implementing John Duffy’s model of speculative learning agents.

1JURIX 05Looks/Loui On Game Mechanisms and Procedural Fairness Moshe Looks Ronald P. Loui Washington University in St. Louis, USA.

Game-theoretic analysis tools Tuomas Sandholm Professor Computer Science Department Carnegie Mellon University.

Lecture 7 Course Summary The tools of strategy provide guiding principles that that should help determine the extent and nature of your professional interactions.

Artificial intelligence methods in the CO 2 permission market simulation Jarosław Stańczak *, Piotr Pałka **, Zbigniew Nahorski * * Systems Research Institute,

Introduction Negotiation is something that everyone does, almost daily 1-1.

Lecture 5 Financial Incentives This lecture is paired with our previous one that discussed employee benefits. Here we focus on the reasons why monetary.

An Extended Alternating-Offers Bargaining Protocol for Automated Negotiation in Multi-agent Systems P. Winoto, G. McCalla & J. Vassileva Department of.

1 What is Game Theory About? r Analysis of situations where conflict of interests is present r Goal is to prescribe how conflicts can be resolved 2 2 r.

Game Theory Optimal Strategies Formulated in Conflict MGMT E-5070.

Lecture 1 on Bargaining Setting the Agenda This lecture focuses on the well known problem of how to split the gains from trade or, more generally, mutual.

Negotiation Skills Mike Phillips Training Quality Manager

Intermediate Microeconomics Game Theory and Oligopoly.

1. 2 You should know by now… u The security level of a strategy for a player is the minimum payoff regardless of what strategy his opponent uses. u A.

Strategic Game Theory for Managers. Explain What is the Game Theory Explain the Basic Elements of a Game Explain the Importance of Game Theory Explain.

Intermediate Microeconomics Game Theory. So far we have only studied situations that were not “strategic”. The optimal behavior of any given individual.

1 By: Ms. Adina Malik (ALK) Agents, Constituencies, Audiences Coalitions Multiple Parties and Teams By: Ms. Adina Malik (ALK)

Lecture V: Bargaining Recommended Reading: Dixit & Skeath, Chapter 17 Osborne, Chapter 6.1, 16 Powell, In the Shadow of Power, Ch. 3.

John Forbes Nash John Forbes Nash, Jr. (born June 13, 1928) is an American mathematician whose works in game theory, differential geometry, and partial.

Q 2.1 Nash Equilibrium Ben

INTEGRATIVE BARGAINING, CULTURE CLASHES

Unit 4 SOCIAL INTERACTIONS.

Multiagent Systems Game Theory © Manfred Huber 2018.

Game Theory Chapter 12.

CASE − Cognitive Agents for Social Environments

Multiagent Systems Repeated Games © Manfred Huber 2018.

Negotiation skills.

Collaboration in Repeated Games

Normal Form (Matrix) Games

Presentation transcript:

A New Model of Negotiation Based on Pessimism and Punishment Ronald P. Loui Washington University St. Louis CAEPIA 2003

A New Model of Negotiation Based on Pessimism and Punishment Preliminary Remarks CAEPIA 2003

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Preliminary Remarks Logic of Argument Defeat among Arguments Workshop on Defeasibility G. Simari's thesis NATHAN in C H. Prakken's thesis 1993 (1997) - Process & Policy G. Vreeswijk's thesis T. Gordon's thesis B. Verheij's thesis A. Lodder's thesis ACM Computing Surveys

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Preliminary Remarks Logic of Arguments & Cases LMNOP in LISP Argument Game Policies and Precedents Rationales Room5 in GAWK/CGI Prakken-Sartor Bench-Capon Johnston-Governatori

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui "Why does there have to be a winner? Why can't you work on negotiation instead of argument?" -- Prof. Anne Johnstone* *"University of Maine assistant professor of computer science Anne Johnstone died of complications resulting from lung cancer on February 28, After completing her PhD [in Artificial Intelligence at the University of Edinburgh approx. 1990], Anne took a position as senior research associate in the computer science department at Washington University in St. Louis, and while there established a successful research program in natural language processing, funded by Southwestern Bell Technology Resources." ( **This invited talk is dedicated to the memory of my faculty colleague. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis G. Ferguson's thesis Computational Dialectics Workshop Mark Foltz's (WU/MIT) u. thesis Parsons-Jennings Diana Moore's (WU/NSA/EnGarde) u. thesis Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis case-based problem-solving for labor-management disputes = argument G. Ferguson's thesis Computational Dialectics Workshop Mark Foltz's (WU/MIT) u. thesis Parsons-Jennings Diana Moore's (WU/NSA/EnGarde) u. thesis Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis G. Ferguson's thesis "mixed initiative" planning = mixture of argument & negotiation Computational Dialectics Workshop Mark Foltz's (WU/MIT) u. thesis Parsons-Jennings Diana Moore's (WU/NSA/EnGarde) u. thesis Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis G. Ferguson's thesis Computational Dialectics Workshop notation & protocol for proposal, threat, inform, justify, etc. as speech acts Mark Foltz's (WU/MIT) u. thesis Parsons-Jennings Diana Moore's (WU/NSA/EnGarde) u. thesis Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis G. Ferguson's thesis Computational Dialectics Workshop Mark Foltz's (WU/MIT) u. thesis 1. Cooperative protocol level: reciprocal progress 2. Cooperative protocol level: immediate response 3. Cooperative protocol level: arguing for proposals 4. Uncooperative protocol level: using threats Parsons-Jennings Diana Moore's (WU/NSA/EnGarde) u. thesis Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis G. Ferguson's thesis Computational Dialectics Workshop Mark Foltz's (WU/MIT) u. thesis Parsons-Jennings uses Fox's argument logic for formalizing arguments about proposals Diana Moore's (WU/NSA/EnGarde) u. thesis Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis G. Ferguson's thesis Computational Dialectics Workshop Mark Foltz's (WU/MIT) u. thesis Parsons-Jennings Diana Moore's (WU/NSA/EnGarde) u. thesis list of speech acts in negotiation dialogue, including: o change of focus o request for proposal o "settlement" as a linguistic object (a contract) Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis G. Ferguson's thesis Computational Dialectics Workshop Mark Foltz's (WU/MIT) u. thesis Parsons-Jennings Diana Moore's (WU/NSA/EnGarde) u. thesis Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation K. Sycara's thesis G. Ferguson's thesis Computational Dialectics Workshop Mark Foltz's (WU/MIT) u. thesis Parsons-Jennings Diana Moore's (WU/NSA/EnGarde) u. thesis Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. Main Idea: One may argue for or against a proposal (a proposed settlement). Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Argument and Negotiation 1970's - R. Fisher-(Ury-Patton) "principled negotiation" … Jennings-Parsons-Noriega, Sierra-Jennings, Jennings-Parsons- Noriega-Sierra, Parsons-Sierra-Jennings, Jennings-Faratin-Lomuscio-Parsons- Wooldridge-Sierra, etc. UN-ANSWERED QUESTION: What cost is incurred by the party to a negotiation who refuses the consequences of rational argument? Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm S. Lander's thesis CMU talk Strategic directions in AI (ACM Computing Surveys) T. Sandholm's thesis Kay Hashimoto (Harvard/FJC) Diana Moore's (WU/NSA/EnGarde) u. thesis Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm "strategy for reducing overall computation costs" by trading tasks, TSP's S. Lander's thesis CMU talk Strategic directions in AI (ACM Computing Surveys) T. Sandholm's thesis Kay Hashimoto (Harvard/FJC) Diana Moore's (WU/NSA/EnGarde) u. thesis Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm S. Lander's thesis "uses conflict as a source of control information for directing search" CMU talk Strategic directions in AI (ACM Computing Surveys) T. Sandholm's thesis Kay Hashimoto (Harvard/FJC) Diana Moore's (WU/NSA/EnGarde) u. thesis Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm S. Lander's thesis CMU talk consider the strategic form payoffs to be heuristic! Strategic directions in AI (ACM Computing Surveys) T. Sandholm's thesis Kay Hashimoto (Harvard/FJC) Diana Moore's (WU/NSA/EnGarde) u. thesis Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm S. Lander's thesis CMU talk Strategic directions in AI (ACM Computing Surveys) "Instead of starting with a matrix of payoffs to each player … introduce a structure that can be altered through computation" T. Sandholm's thesis Kay Hashimoto (Harvard/FJC) Diana Moore's (WU/NSA/EnGarde) u. thesis Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm S. Lander's thesis CMU talk Strategic directions in AI (ACM Computing Surveys) T. Sandholm's thesis Negotiation Among Self-Interested Computationally Limited Agents Kay Hashimoto (Harvard/FJC) Diana Moore's (WU/NSA/EnGarde) u. thesis Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm S. Lander's thesis CMU talk Strategic directions in AI (ACM Computing Surveys) T. Sandholm's thesis Kay Hashimoto (Harvard/FJC) each agent solves non-linear constrained optimization, asks "why not", responds with list of binding constraints Diana Moore's (WU/NSA/EnGarde) u. thesis Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm S. Lander's thesis CMU talk Strategic directions in AI (ACM Computing Surveys) T. Sandholm's thesis Kay Hashimoto (Harvard/FJC) Diana Moore's (WU/NSA/EnGarde) u. thesis o can search: your problem OR partner's problem; o the simplest formal model of utility-revision / joint problem-solving Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation pre-Lesser Sandholm K. Decker's thesis, Sandholm-Lesser Strategic directions in AI / ACM Computing Surveys T. Sandholm's thesis Diana Moore's (WU/NSA/EnGarde) u. thesis Kay Hashimoto (Harvard/FJC). Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks 2?6?9?11? 5?8?10?13? 7?9?10?15?

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks 2?6?9?11? 5?8?10?13? 7?9?10?15? proposed

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks 2?6?9?11? 5?8?11?13? 7?9?10?15? proposed …search…

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks 2?6?9?11? 5?8?11?13? 7?9?10?15? proposed …search…

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks 2?6?9?11? 5?8?11?13? 7?9?10?15? proposed …search…

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks 2?6?9?11? 5?8?13? 7?9?10?15? proposed …search…

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! Main Idea: Payoffs (in strategic form) are not fixed, but can change with search. Preliminary Remarks 2?6?9?11? 5?8?16?13? 7?9?10?15? proposed …search… accepted

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! UN-ANSWERED QUESTION: Is it rational to accept a proposal if its heuristic valuation looks good JUST BECAUSE more time was spent searching to make it look good? Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation OBSERVATION: If anytime search is focused on proposals then agreement is easier to achieve! UN-ANSWERED QUESTION: Is it rational to accept a proposal if its heuristic valuation looks good JUST BECAUSE more time was spent searching to make it look good? Preliminary Remarks Sandholm: Look for deliberation equilibria!

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation Preliminary Remarks Sandholm: Look for deliberation equilibria! Loui: Equilibrium is a silly idea! Negotiation is a process. How about looking at trajectories?

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Search and Negotiation Anne Jump (Harvard) Negotiation game Preliminary Remarks

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui

A New Model of Negotiation Based on Pessimism and Punishment CAEPIA 2003 *thanks to F. Tohme, K. Larson, S. Braynov, J. Nachbar, B. Dheeravongkit, L. Cai, K. Chin, R. Bujans, M. Looks, E. Wofsey, J. Rosen, S. Grubor, K. Ormsby, J. Badino, R. Pless, and M.A. Clark.

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements Party 1's aspiration Party 2's aspiration

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements Party 2's proposals at t Party 1's proposals at t

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements inadmissible (dominated) at t

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements In black: admissible settlements at t (probability of agreement Is non-zero)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements Breakdown row Breakdown column

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements Breakdown would occur here (BATNA)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements 1's aspiration 2's aspiration

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements Breakdown (BATNA)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements Breakdown (BATNA)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements Rising probability of break down

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements 1's security level 2's security level 2 would rather break down 1 would rather break down

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: parties to a negotiation (can) construct a probability distribution over potential settlements Eu 1 |s = 51 Eu 2 |s = 49α +54(1-α) Prob(bd) = ?

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Observation: From probability, one may calculate 1. An expected utility given settlement (Eu|s) and 2. An expected utility given continued negotiation, Eu = Eu|s (1 - prob(bd)) + u(bd) prob(bd) Observation: It may be rational to 1. Extend an offer, o, if Eu < u(o) 2. Accept an offer, acc, if Eu < u(acc), acc  offers(t) 3. Break down unilaterally if Eu < security

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Probability here is OBJECTIVE PROBABILITY: 1. It is based on data and induction 2. Given the data (and method), prob is fixed 3. Cannot subjectively will the prob to be different (see Keynes) Rationality here is CONSTRUCTIVE RATIONALITY: 1. Action may be justified in a variety of ways 2. Expected utility is one way to justify action 3. These constraints are one-sided: (permissions, not prohibitions) (see Simon/Shafer/Tversky)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui To construct prob(bd|situation), consider similar past situations in which: 1. Similar stakes & securities 2. Similar negotiating partners 3. Similar progress … (see Kyburg) The one-sided constraint is similar to: bargaining representative of a union with proxy to act but not to censor union action (probabilities are of independent union action) But is here a general model of rationality for a single mind (see Minsky)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui (Empirical) Claim. Pessimism For sufficiently large Δ, for all t: prob(bd | NP(t+Δ)) > prob(bd | NP(t)) where NP(t) denotes non-progress for a period t What is progress? A non-trivial offer by the other party What does this mean? (at some granularity, the past record implies that:) If there are no offers, the likelihood of breakdown rises

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui (Empirical) Claim. Pessimism For sufficiently large Δ, for all t: prob(bd | NP(t+Δ)) > prob(bd | NP(t)) where NP(t) denotes non-progress for a period t Linear Pessimism prob(bd | NP(t)) = π t Exponential Pessimism prob(bd | NP(t)) = 1 - e -πt

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Pessimism causes Eu to fall Next offer is made at this time and prob(bd) resets to 0 Expectation starts to fall again

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui reciprocated offers offers

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Agreement reached as Eu < u1

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui security Best offer received Whenever u(acc) > security, acceptance occurs before breakdown!

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui security Best offer received Would you accept an 11-cent offer if your security were 10-cents?

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Design Idea. Resentment u(bd) = security + resentment(t) s.t. NP(t) where NP(t) denotes non-progress for a period t What is resentment? 1. Dignity 2. Pride 3. Investment in society 4. Protection against non-progressive manipulators

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Design Idea. Resentment u(bd) = security + resentment(t) s.t. NP(t) where NP(t) denotes non-progress for a period t What is resentment? 5. Non-standard utility (process or transactional utility) 6. Re: procedural fairness, not substantive fairness 7. A (speech act) distinction: vs. BD! 8. specific (BD! by ME on YOU) vs. indifferent (BD!)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Design Idea. Resentment u(bd) = security + resentment(t) s.t. NP(t) where NP(t) denotes non-progress for a period t linear resentment r(t) = ρt sigmoid resentment r(t) = r max (2/(1+e -ρt ) -1)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Breaks down instead of agreeing because of rising resentment security+resentment security

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Actually accepts because resentment resets with progress Resentment resets to zero Nontrivial progess

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Resentment does not reset to zero Agent breaks down before accepting

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Variety of Behaviors Agent can wait, then offer Agent can wait, then accept Agent can wait, then break down Agent can accept immediately Agent can offer before accepting and vice versa Agent can breakdown before accepting and vice versa Agent can offer before breaking down and vice versa Agent can be on path to breakdown, then on path to acceptance because received offer changes Eu or resentment because extended offer changes Eu

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui low-valued ρ high-valued ρ (Assumes no progress)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui low-valued ρ high-valued ρ (Assumes no progress)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui (Assumes no progress) low-valued ρ high-valued ρ

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui rare alternation (Assumes no progress)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui What happens when two P&P agents interact? Dominated by BATNA 1's offers in this round 2's offer in this round Eu 2 2's aspiration BATNA = 1's aspirationEu 1

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui What happens when two P&P agents interact? Eu 2 Eu 1 (t=2)Eu 1 (t=1)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui What happens when two P&P agents interact? 1's security+ resentment 2's security+ resentment 1's offers in this round

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui What happens when two P&P agents interact?

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui What happens when two P&P agents interact?

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui What happens when two P&P agents interact? 1 breaks down Amount of (specific) resentment Laissez-faire path is through time

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Does the starting offer affect the laissez-faire path? Both generous at the start 1 is generous at start, 2 is not 2 is generous at start, 1 is not

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Breakdown at t=2 (pure pessimism)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Different laissez-faire paths

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Breakdown at t=5 with resentment

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui All paths lead to breakdown

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui In a different negotiation, some paths lead to acceptance, some to breakdown Fixed agent characteristics Varied acceleration of offers

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui A third example where player 1 can guarantee an acceptance outcome with the right initial offers

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Laissez-Faire Paths What are they? They are the path taken if Eu drives all speech acts (offers, acceptance, and breakdown) BUT rationality is constructive: constraints are one-sided, specifying latest times, not earliest times One may deviate from the path by accelerating offers take initiative show free will, self-determination

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Laissez-Faire Paths What are they? They are the path taken if Eu drives all speech acts (offers, acceptance, and breakdown) So how about a meta-game over the "when to accelerate offers" strategy space? We could find Nash Equilibria!

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Laissez-Faire Paths What are they? They are the path taken if Eu drives all speech acts (offers, acceptance, and breakdown) So how about a meta-game over the "when to accelerate offers" strategy space? We could find Nash Equilibria! OK, but it is a control problem (like flying an airplane): estimation and correction Are we on a path to agreement? Does other party need new reason to continue?

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui All sorts of meta-games whenever you combine laissez-faire behavior and elective initiative-taking…

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui All sorts of meta-games whenever you combine laissez-faire behavior and elective initiative-taking… Payoffs adjusted for substantive fairness, time, concessions, aspiration, and security

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Desiderata for an AI model of negotiation Should be able to participate in the process of negotiation: make offers, respond to offers, deliberate upon offers, (even threaten, search, argue…) NOT just insist on a solution Should model the phenomenon directly: pessimism, expectation, security, resentment… NOT just implement a mathematical analysis

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Desiderata for an AI model of negotiation Should be able to participate in the process of negotiation: make offers, respond to offers, deliberate upon offers, (even threaten, search, argue…) NOT just insist on a solution Should model the phenomenon directly: pessimism, expectation, security, resentment… NOT just implement a mathematical analysis Should be robust in poor information settings: there may be no common knowledge, no model of other's mental states (our model is decoupled!) Should learn about negotiating partner and social norms: offline, objective probability is based on data; online estimation is anticipated (agent can be calibrated)

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Desiderata for an AI model of negotiation Should be able to participate in the process of negotiation: make offers, respond to offers, deliberate upon offers, (even threaten, search, argue…) NOT just insist on a solution Should model the phenomenon directly: pessimism, expectation, security, resentment… NOT just implement a mathematical analysis Should be robust in poor information settings: there may be no common knowledge, no model of other's mental states (our model is decoupled!) Should learn about negotiating partner and social norms: offline, objective probability is based on data; online estimation is anticipated (agent can be calibrated) Should be an architectural paradigm for design of agents: pessimism and resentment are internally balancing forces; this is a design proposal, not an empirical claim

CAEPIA-2003 San SebastianA New Model of Negotiation Based on Pessimism and Punishment – R. P. Loui Desiderata for an AI model of negotiation Should be able to participate in the process of negotiation: make offers, respond to offers, deliberate upon offers, (even threaten, search, argue…) NOT just insist on a solution Should model the phenomenon directly: pessimism, expectation, security, resentment… NOT just implement a mathematical analysis Should be robust in poor information settings: there may be no common knowledge, no model of other's mental states (our model is decoupled!) Should learn about negotiating partner and social norms: offline, objective probability is based on data; online estimation is anticipated (agent can be calibrated) Should be an architectural paradigm for design of agents: pessimism and resentment are internally balancing forces; this is a design proposal, not an empirical claim much work to be done!

A New Model of Negotiation Based on Pessimism and Punishment R. P. Loui Washington University St. Louis CAEPIA 2003 thanks to M. Foltz, V. Reddy, D. Weisberger, I. Figelman, D. Moore, K. Hashimoto, A. Jump, F. Tohme, K. Larson, S. Braynov, J. Nachbar, B. Dheeravongkit, L. Cai, K. Chin, R. Bujans, M. Looks, E. Wofsey, J. Rosen, S. Grubor, K. Ormsby, J. Badino, R. Pless, and M.A. Clark.

A New Model of Negotiation Based on Pessimism and Punishment R. P. Loui Washington University St. Louis CAEPIA 2003 thanks to M. Foltz, V. Reddy, D. Weisberger, I. Figelman, D. Moore, K. Hashimoto, A. Jump, F. Tohme, K. Larson, S. Braynov J. Nachbar, B. Dheeravongkit, L. Cai, K. Chin, M. Looks,R. Wofsey, J. Rosen, S. Grubor, K. Ormsby, J. Badino, R. Pless, and M.A. Clark. Research Funding from: NSF Information Technology and Organizations Program: Multi-Agent Negotiation, as co-PI with T. Sandholm, July 1997 to July NSF Office of Cross-Disciplinary Affairs and Interactive Systems Program: Summer Undergraduate Research Assistants, March 1995 to February NSF Office of Cross-Disciplinary Affairs: REU Continuing Award, April 1992 to September