Abstract. Experimentalists frequently claim that human subjects in the laboratory violate game-theoretic predictions. It is here argued that this claim is usually premature. The paper elaborates on this theme by way of raising some conceptual and methodological issues in connection with the very definition of a game and of players ’ preferences, in particular with respect to potential context dependence, interpersonal preference dependence, backward induction and incomplete information.

Most economic models are based on the self-interest hypothesis that assumes that all people are exclusively motivated by their material self-interest. In recent years experimental economists have gathered overwhelming evidence that systematically refutes the self-interest hypothesis and suggests that many people are strongly motivated by concerns for fairness and reciprocity. Moreover, several theoretical papers have been written showing that the observed phenomena can be explained in a rigorous and tractable manner. These theories in turn induced a new wave of experimental research offering additional exciting insights into the nature of preferences and into the relative performance of competing theories of fairness. The purpose of this paper is to review these recent developments, to

The language of game theory—coalitions, payo¤s, markets, votes— suggests that it is not a branch of abstract mathematics; that it is motivated by and related to the world around us; and that it should be able to

Abstract: Many public policy debates can be characterized as disagreements among multiple stakeholders about the selection of a public good that has multiple attributes. A common method for resolving such disputes is collaborative decision-making, in which representatives of interest groups negotiate new policies “in the shadow ” of government-imposed backstop policies. Although this technique is widely used, little is known about the nature of the policies that it generates. The purpose of this paper is to identify several hypotheses about collaborative decision-making using the Edgeworth box framework, and to test these hypotheses using laboratory experiments. Specifically, we investigate the predictive success of three theories of negotiator motivation: utilitarian (attraction to the Nash bargain), egalitarian (equalization of the parties ’ payoffs), and historical entitlement (maintenance of the status quo, or “historical ” distribution of payoffs). Using a full information, face-to-face bargaining design, we find that parties successfully reach approximately Pareto efficient agreements. When the Nash bargain differs from the efficient outcome at which payoffs are equalized, our subjects are drawn partially towards the latter. When the

Abstract Negotiation has been studied in different communities both scientific and communities of practice. The social sciences and the mathematical sciences have investigated different aspects of negotiation with different goals: the goals of the social sciences are to understand the factors and reasoning processes that underlie human negotiation behavior. The goal of the mathematical sciences is to formulate mathematical models that capture elements of negotiation. Further, the mathematical models can be divided into analytic models (economic, operations research etc) and computational models. The aim of the analytic models is to provide guarantees of their behavior, characterizations of optimality, or provide managerial guidance to optimize negotiation activity. The computational models aim to provide computational tractability through approximation algorithms and heuristics. Most crucially, the computational research aims to have the models implemented in autonomous processes, called agents, that are able to incorporate realistic factors of negotiation (e.g. argumentation, information seeking, and cognitive factors) and engage in negotiations in a decentralized manner. Such agent models promise to contribute to our understanding of human information processing in negotiation. Additionally, they could be used for decision support of human decision makers. In the long run, such models can even become substitutes for human negotiators. In this chapter we will provide a selective review of the most important works in the analytic and computational negotiation literature, point out some differences and synergies and provide pointers to open questions and future research.