Opponent's Utility Research Articles

Weighting Estimation Methods for Opponents' Utility Functions Using Boosting in Multi-Time Negotiations

Recently, multi-issue closed negotiations have attracted attention in multi-agent systems. In particular, multitime and multi-lateral negotiation strategies are important topics in multi-issue closed negotiations. In multi-issue closed negotiations, an automated negotiating agent needs to have strategies for estimating an opponent's utility function by learning the opponent's behaviors since the opponent's utility information is not open to others. However, it is difficult to estimate an opponent's utility function for the following reasons: (1) Training datasets for estimating opponents' utility functions cannot be obtained. (2) It is difficult to apply the learned model to different negotiation domains and opponents. In this paper, we propose a novel method of estimating the opponents' utility functions using boosting based on the least-squares method and nonlinear programming. Our proposed method weights each utility function estimated by several existing utility function estimation methods and outputs improved utility function by summing each weighted function. The existing methods using boosting are based on the counting method, which counts the number of values offered, considering the time elapsed when they were offered. Our experimental results demonstrate that the accuracy of estimating opponents' utility functions is significantly improved under various conditions compared with existing utility function estimation methods without boosting.

Compromising Adjustment Strategy Based on TKI Conflict Mode for Multi‐Times Bilateral Closed Negotiations

Bilateral multi‐issue closed negotiation is an important class for real‐life negotiations. Usually, negotiation problems have constraints such as a complex and unknown opponent's utility in real time, or time discounting. In the class of negotiation with some constraints, the effective automated negotiation agents can adjust their behavior depending on the characteristics of their opponents and negotiation scenarios. Recently, the attention of this study has focused on the interleaving learning with negotiation strategies from the past negotiation sessions. By analyzing the past negotiation sessions, agents can estimate the opponent's utility function based on exchanging bids.In this article, we propose a negotiation strategy that estimates the opponent's strategies based on the past negotiation sessions. Our agent tries to compromise to the estimated maximum utility of the opponent by the end of the negotiation. In addition, our agent can adjust the speed of compromise by judging the opponent's Thomas–Kilmann conflict mode and search for the Pareto frontier using past negotiation sessions. In the experiments, we demonstrate that the proposed agent has better outcomes and greater search technique for the Pareto frontier than existing agents in the linear and nonlinear utility functions.

Multi-Issue Negotiation with Deadlines

This paper studies bilateral multi-issue negotiation between self-interested autonomous agents. Now, there are a number of different procedures that can be used for this process; the three main ones being the package deal procedure in which all the issues are bundled and discussed together, the simultaneous procedure in which the issues are discussed simultaneously but independently of each other, and the sequential procedure in which the issues are discussed one after another. Since each of them yields a different outcome, a key problem is to decide which one to use in which circumstances. Specifically, we consider this question for a model in which the agents have time constraints (in the form of both deadlines and discount factors) and information uncertainty (in that the agents do not know the opponent's utility function). For this model, we consider issues that are both independent and those that are interdependent and determine equilibria for each case for each procedure. In so doing, we show that the package deal is in fact the optimal procedure for each party. We then go on to show that, although the package deal may be computationally more complex than the other two procedures, it generates Pareto optimal outcomes (unlike the other two), it has similar earliest and latest possible times of agreement to the simultaneous procedure (which is better than the sequential procedure), and that it (like the other two procedures) generates a unique outcome only under certain conditions (which we define).

Tit for tat: Foundations of preferences for reciprocity in strategic settings

This paper assumes that in addition to conventional preferences over outcomes, players in a strategic environment have preferences over strategies. It provides conditions under which a player's preferences over strategies can be represented as a weighted average of the utility from outcomes of the individual and his opponents. The weight one player places on an opponent's utility from outcomes depends on the players’ joint behavior. In this way, the framework is rich enough to describe the behavior of individuals who repay kindness with kindness and meanness with meanness. The paper identifies restrictions that the theory places on rational behavior.

On arguments from self-interest for the Nash solution and the Kalai egalitarian solution to the bargaining problem

I argue in this paper that there are two considerations which govern the dynamics of a two-person bargaining game, viz. relative proportionate utility loss from conceding to one's opponent's proposal and relative non-proportionate utility loss from not conceding to one's opponent's proposal, if she were not to concede as well. The first consideration can adequately be captured by the information contained in vNM utilities. The second requires measures of utility which allow for an interpersonal comparison of utility differences. These considerations respectively provide for a justification of the Nash solution and the Kalai egalitarian solution. However, none of these solutions taken by themselves can provide for a full story of bargaining, since, if within a context of bargaining one such consideration is overriding, the solution which does not match this consideration will yield unreasonable results. I systematically present arguments to the effect that each justification from self-interest for respectively the Nash and the Kalai egalitarian solution is vulnerable to this kind of objection. I suggest that the search for an integrative model may be a promising line of research.

The Role of Attitude Toward Risk in Strictly Competitive Decision-Making Situations

The impact of decision makers' attitudes toward risk has been studied extensively in the context of noncompetitive decision making but not in the context of competitive decision making. In this paper we study the effects of the utility functions of the players in a strictly competitive decision-making situation on (a) their strategies and (b) their expected monetary payoffs. The setting is that of a two-by-two, two-person, zero-sum (in money) game with exponential utility functions for the competitors. The monetary payoffs and utility functions are assumed to be public knowledge. Combinations of utility functions that preserve the zero-sum condition as well as combinations that do not preserve this condition are considered. As might be expected, results from noncompetitive decision making do not necessarily carry over into competitive situations. For example, an increase in the risk aversion of a player may actually increase that player's expected monetary payoff because of altered strategies on the part of the competitor. In general, the effects of nonlinear utility functions on a player's strategy and expected monetary payoff depend on the player's utility function, the opponent's utility function, and the relationship among the entries in the payoff table. Furthermore, it does not appear possible to express this dependence in the form of simple rules of thumb, although the results presented here indicate the direction of movement of strategies and expected payoffs as the inputs to the problem are varied in certain systematic ways.

Bargaining in ignorance of the opponent's utility function

1 The original version of this paper was written at the Cowles Foundation for Research in Economics at Yale University, under Contract Nonr-358 (01), NR 047-006 of the Cowles Foundation with the Office of Naval Research. It was distributed as Cowles Foundation Discussion Paper No. 46. A revised version of this paper was presented at the Princeton Conference on Game Theory and Negotiations in October, 1961. The paper has benefited from comments by the other participants of the Conference. 2 But of course there are exceptions. For a model dealing with the case where the players do not know one another's utility functions, see (Luce and Adams, 1956). know (and know they do not know) each other's utility functions. I shall also indicate some interesting problems our analysis raises for empirical research.