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Provides a unified, coherent account of machine interaction at the level of the machine designers (the society of designers) and the level of the machine interaction itself (the resulting artificial society). Rules of Encounter applies the general approach and the mathematical tools of game theory in a formal analysis of rules (or protocols) governing the high-level behavior of interacting heterogeneous computer systems. It describes a theory of high-level protocol design that can be used to constrain manipulation and harness the potential of automated negotiation and coordination strategies to attain more effective interaction among machines that have been programmed by different entities to pursue different goals. While game theoretic ideas have been used to answer the question of how a computer should be programmed to act in a given specific interaction, here they are used in a new way, to address the question of how to design the rules of interaction themselves for automated agents. Rules of Encounter provides a unified, coherent account of machine interaction at the level of the machine designers (the society of designers) and the level of the machine interaction itself (the resulting artificial society). Taking into account such attributes of the artificial society as efficiency, and the self-interest of each member in the society of designers, it analyzes what kinds of rules should be instituted to govern interaction among these autonomous agents. The authors point out that adjusting the rules of public behavior--or the rules of the game--by which the programs must interact can influence the private strategies that designers set up in their machines, shaping design choices and run-time behavior, as well as social behavior. Artificial Intelligence series

Abstract: "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 sub-additive domains, there often exist beneficial decoy lies that do not require full information regarding the other agent's goals."

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 (that is, agents in fundamental conflict might still agree to cooperate up to a certain point). 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 (i.e., one that does not achieve all agents' goals) might be preferred by all agents, even though there exists a rational agreement that would achieve all their goals."

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."