Gilad Zlotkin

Multiagent negotiation under time constraints

Research in distributed artificial intelligence (DAI) is concerned with how automated agents can be designed to interact effectively. Negotiation is proposed as a means for agents to communicate and compromise to reach mutually beneficial agreements. The paper examines the problems of resource allocation and task distribution among autonomous agents which can benefit from sharing a common resource or distributing a set of common tasks. We propose a strategic model of negotiation that takes the passage of time during the negotiation process itself into account. A distributed negotiation mechanism is introduced that is simple, efficient, stable, and flexible in various situations. The model considers situations characterized by complete as well as incomplete information, and ones in which some agents lose over time while others gain over time. Using this negotiation mechanism autonomous agents have simple and stable negotiation strategies that result in efficient agreements without delays even when there are dynamic changes in the environment.

Designing conventions for automated negotiation

■ As distributed systems of computers play an increasingly important role in society, it will be necessary to consider ways in which these machines can be made to interact effectively. We are concerned with heterogeneous, distributed systems made up of machines that have been programmed by different entities to pursue different goals. Adjusting the rules of public behavior (the rules of the game) by which the programs must interact can influence the private strategies that designers set up in their machines. These rules can shape the design choices of the machines’ programmers and, thus, the run-time behavior of their creations. Certain kinds of desirable social behavior can thus be caused to emerge through the careful design of interaction rules. Formal tools and analysis can help in the appropriate design of these rules. We consider how concepts from fields such as decision theory and game theory can provide standards to be used in the design of appropriate negotiation and interaction environments. This design is highly sensitive to the domain in which the interaction is taking place. This article is adapted from an invited lecture given by Jeffrey Rosenschein at the Thirteenth International Joint Conference on Artificial Intelligence in Chambery, France, on 2 September 1993.

Cooperation and conflict resolution via negotiation among autonomous agents in noncooperative domains

The authors present a theoretical negotiation model for rational agents in general noncooperative domains. Necessary and sufficient conditions for cooperation are outlined. By redefining the concept of utility, it is possible to enlarge the number of situations that have a cooperative solution. An approach is offered for conflict resolution, and it is shown that even in a conflict situation, partial cooperative steps can be taken by interacting agents. A unified negotiation protocol is developed that can be used in all cases. It is shown that in certain borderline cooperative situations, a partial cooperative agreement might be preferred by all agents, even though there exists a rational agreement that would achieve all their goals. A deal hierarchy is presented that captures the partial order among various kinds of deals between agents. The multiplan deal, which involves negotiating over a pair of joint plans simultaneously, allows cooperative agreement and conflict resolution in both fixed goal and flexible goal domains. >

Mechanism design for automated negotiation, and its application to task oriented domains

Abstract As distributed systems of computers play an increasingly important role in society, it will be necessary to consider ways in which these machines can be made to interact effectively. Especially when the interacting machines have been independently designed, it is essential that the interaction environment be conducive to the aims of their designers. These designers might, for example, wish their machines to behave efficiently, and with a minimum of overhead required by the coordination mechanism itself. The rules of interaction should satisfy these needs, and others. Formal tools and analysis can help in the appropriate design of these rules. We here consider how concepts from game theory can provide standards to be used in the design of appropriate negotiation and interaction environments. This design is highly sensitive to the domain in which the interaction is taking place. Different interaction mechanisms are suitable for different domains, if attributes like efficiency and stability are to be maintained. We present a general theory that captures the relationship between certain domains and negotiation mechanisms. The analysis makes it possible to categorize precisely the kinds of domains in which agents find themselves, and to use the category to choose appropriate negotiation mechanisms. The theory presented here both generalizes previous results, and allows agent designers to characterize new domains accurately. The analysis thus serves as a critical step in using the theory of negotiation in real-world applications. We show that in certain task oriented domains, there exist distributed consensus mechanisms with simple and stable strategies that lead to efficient outcomes, even when agents have incomplete information about their environment. We also present additional novel results, in particular that in concave domains using all-or-nothing deals, no lying by an agent can be beneficial, and that in subadditive domains, there often exist beneficial decoy lies that do not require full information regarding the other agents goals.

Meet your destiny: a non-manipulable meeting scheduler

In this paper we present three scheduling mechanisms that are manipulation-proof for closed systems. The amount of information that each user must encode in the mechanism increases with the complexity of the mechanism. On the other hand, the more complex the mechanism is, the more it maintains the privacy of the users. The first mechanism is a centralized, calendar-oriented one. It is the least computationally complex of the three, but does not maintain user privacy. The second is a distributed meeting-oriented mechanism that maintains user privacy, but at the cost of greater computational complexity. The third mechanism, while being the most complex, maintains user privacy (for the most part) and allows users to have the greatest influence on the resulting schedule.

The case of the lying postman: Decoys and deception in negotiation

Much research in negotiation assumes complete knowledge among the interacting agents and/or truthful agents. These assumptions in many domains will not be realistic, and this paper extends our previous work in dealing with the case of inter-agent negotiation with incomplete information. A discussion of our existing negotiation framework sets out the rules by which agents operate during this phase of their interaction. The concept of a “solution” within this framework is presented; the same solution concept serves for interactions between agents with incomplete information as it does for complete information interactions. The possibility of incomplete information among agents opens up the possibility of deception as part of the negotiation strategy of an agent. Deception during negotiation among autonomous agents is thus analyzed in the Postmen Domain, which was introduced by us in a previous paper. New results regarding the non-beneficial nature of lies is presented. It is shown that hiding letters can be beneficial when negotiation is conducted over mixed deals. When the Postmen Domain is restricted to graphs having a tree topology, then it is shown that decoy letters (manufactured by a lying agent) cannever be beneficial, and that no combination of types of lies is beneficial when negotiation is conducted over all-or-nothing deals.