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 area of automated negotiation has been of particular interest in artificial intelligence due to the important role negotiation plays in facilitating understanding and achieving co-operation among entities with differing interests. These entities may be individuals, organizations, governments, or automated agents. This paper presents methods for solving different aspects of automated negotiation: with whom to negotiate, evaluation of suggestions and the way to offer suggestions. These methods were successfully used to develop the system Diplomat, that may be one of the players in a board game, Diplomacy. This game is characterized by intense negotiation, a very large set of possible strategies and the absence of a trusted intermediary. Although Diplomacy players may break their promises, close co-operation is needed for a success.