Jeffrey S. Rosenschein

Deals among rational agents

A formal framework is presented that models communication and promises in multi-agent interactions. This framework generalizes previous work on cooperation without communication, and shows the ability of communication to resolve conflicts among agents having disparate goals. Using a deal-making mechanism, agents are able to coordinate and cooperate more easily than in the communication-free model. In addition, there arc certain types of interactions where communication makes possible mutually beneficial activity that is otherwise impossible to coordinate.

Cooperation without communication

Intelligent agents must be able to interact even without the benefit of communication. In this paper we examine various constraints on the actions of agents in such situations and discuss the effects of these constraints on their derived utility. In particular, we define and analyze basic rationality; we consider various assumptions about independence; and we demonstrate the advantages of extending the definition of rationality from individual actions to decision procedures.

Junta distributions and the average-case complexity of manipulating elections

Encouraging voters to truthfully reveal their preferences in an election has long been an important issue. Recently, computational complexity has been suggested as a means of precluding strategic behavior. Previous studies have shown that some voting protocols are hard to manipulate, but used NP-hardness as the complexity measure. Such a worst-case analysis may be an insufficient guarantee of resistance to manipulation. Indeed, we demonstrate that NP-hard manipulations may be tractable in the average-case. For this purpose, we augment the existing theory of average-case complexity with some new concepts. In particular, we consider elections distributed with respect to junta distributions, which concentrate on hard instances. We use our techniques to prove that scoring protocols are susceptible to manipulation by coalitions, when the number of candidates is constant.

A specification of the Agent Reputation and Trust (ART) testbed: experimentation and competition for trust in agent societies

A diverse collection of trust-modeling algorithms for multi-agent systems has been developed in recent years, resulting in significant breadth-wise growth without unified direction or benchmarks. Based on enthusiastic response from the agent trust community, the Agent Reputation and Trust (ART) Testbed initiative has been launched, charged with the task of establishing a testbed for agent trust- and reputation-related technologies. This testbed serves in two roles: (1) as a competition forum in which researchers can compare their technologies against objective metrics, and (2) as a suite of tools with flexible parameters, allowing researchers to perform customizable, easily-repeatable experiments. This paper first enumerates trust research objectives to be addressed in the testbed and desirable testbed characteristics, then presents a competition testbed specification that is justified according to these requirements. In the testbeds artwork appraisal domain, agents, who valuate paintings for clients, may gather opinions from other agents to produce accurate appraisals. The testbeds implementation architecture is discussed briefly, as well.

Research directions for service-oriented multiagent systems

Todays service-oriented systems realize many ideas from the research conducted a decade or so ago in multiagent systems. Because these two fields are so deeply connected, further advances in multiagent systems could feed into tomorrows successful service-oriented computing approaches. This article describes a 15-year roadmap for service-oriented multiagent system research.

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. >

On the complexity of achieving proportional representation

We demonstrate that winner selection in two prominent proportional representation voting systems is a computationally intractable problem—implying that these systems are impractical when the assembly is large. On a different note, in settings where the size of the assembly is constant, we show that the problem can be solved in polynomial time.

Supporting Privacy in Decentralized Additive Reputation Systems

Previous studies have been suggestive of the fact that reputation ratings may be provided in a strategic manner for reasons of reciprocation and retaliation, and therefore may not properly reflect the trustworthiness of rated parties. It thus appears that supporting privacy of feedback providers could improve the quality of their ratings. We argue that supporting perfect privacy in decentralized reputation systems is impossible, but as an alternative present three probabilistic schemes that support partial privacy. On the basis of these schemes, we offer three protocols that allow ratings to be privately provided with high probability in decentralized additive reputation systems.

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.