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Lecture

Real World Games: Negotiation Strategies

In course

CS-430: Intelligent agents

Software agents are widely used to control physical, economic and financial processes. The course presents practical methods for implementing software agents and multi-agent systems, supported by programming exercises, and the theoretical underpinnings inc ...

Description

This lecture explores real-world games where agents face uncertainty and negotiate to achieve better outcomes than Nash equilibrium. Topics include games with uncertain utilities, Bayes-Nash equilibrium, prisoner's dilemma, correlated equilibrium, and strategic negotiation frameworks. The instructor discusses various negotiation protocols, such as the Nash solution protocol and monotonic concession protocol, to reach optimal agreements.

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Instructor

Boi Faltings

Professor Faltings joined EPFL in 1987 as professor of Artificial Intelligence. He holds a PhD degree from the University of Illinois at Urbana-Champaign, and a diploma from the ETHZ. His research has spanned different areas of intelligent systems linked to model-based reasoning. In particular, he has contributed to qualitative spatial reasoning, case-based reasoning (especially for design problems), constraint satisfaction for design and logistics problems, multi-agent systems, and intelligent user interfaces. His current work is oriented towards multi-agent systems and social computing, using concepts of game theory, constraint optimization and machine learning. In 1999, Professor Faltings co-founded Iconomic Systems, a company that developed a new agent-based paradigm for travel e-commerce. He has since co-founded 5 other startup companies and advised several others. Prof. Faltings has published more than 150 refereed papers on his work, and participates regularly in program committees of all major conferences in the field. He has served as associate editor of of the major journals, including the Journal of Artificial Intelligence Research (JAIR) and the Artificial Intelligence Journal. From 1996 to 1998, he served as head of the computer science department.

Official source

Ontological neighbourhood

Economics

Microeconomics: Game theory

Related concepts (32)

Negotiation

Negotiation is a dialogue between two or more parties to resolve points of difference, gain an advantage for an individual or collective, or craft outcomes to satisfy various interests. The parties aspire to agree on matters of mutual interest. The agreement can be beneficial for all or some of the parties involved. The negotiators should establish their own needs and wants while also seeking to understand the wants and needs of others involved to increase their chances of closing deals, avoiding conflicts, forming relationships with other parties, or maximizing mutual gains.

Negotiation theory

The foundations of negotiation theory are decision analysis, behavioral decision-making, game theory, and negotiation analysis. Another classification of theories distinguishes between Structural Analysis, Strategic Analysis, Process Analysis, Integrative Analysis and behavioral analysis of negotiations. Negotiation is a strategic discussion that resolves an issue in a way that both parties find acceptable. Individuals should make separate, interactive decisions; and negotiation analysis considers how groups of reasonably bright individuals should and could make joint, collaborative decisions.

Nash equilibrium

In game theory, the Nash equilibrium, named after the mathematician John Nash, is the most common way to define the solution of a non-cooperative game involving two or more players. In a Nash equilibrium, each player is assumed to know the equilibrium strategies of the other players, and no one has anything to gain by changing only one's own strategy. The principle of Nash equilibrium dates back to the time of Cournot, who in 1838 applied it to competing firms choosing outputs.

Measurement uncertainty

In metrology, measurement uncertainty is the expression of the statistical dispersion of the values attributed to a measured quantity. All measurements are subject to uncertainty and a measurement result is complete only when it is accompanied by a statement of the associated uncertainty, such as the standard deviation. By international agreement, this uncertainty has a probabilistic basis and reflects incomplete knowledge of the quantity value. It is a non-negative parameter.

Correlated equilibrium

In game theory, a correlated equilibrium is a solution concept that is more general than the well known Nash equilibrium. It was first discussed by mathematician Robert Aumann in 1974. The idea is that each player chooses their action according to their private observation of the value of the same public signal. A strategy assigns an action to every possible observation a player can make. If no player would want to deviate from their strategy (assuming the others also don't deviate), the distribution from which the signals are drawn is called a correlated equilibrium.

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