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