Plan recognition in cooperative or adversarial situations requires
the ability to reason with beliefs. The problem is complicated in
adversarial situations because an opponent may employ deception. In
this case, an agent must also be able to reason about an opponent's
beliefs (nested beliefs) as well as his own beliefs. A system has been
developed that permits agents to reason with nested beliefs using
possible worlds semantics; consistency maintenance is employed to allow
agents to revise their beliefs when an inconsistency occurs. The
advantages over prior systems are that belief revision occurs without
user interaction and that beliefs are treated as objects having equal
status with facts; this permits complex interaction between beliefs and
actions. The theory includes treatment of many areas necessary to
create a system of multiple autonomous reasoning agents. These agents
are given the ability to deceive each other and to predict when they
are being deceived. The system is shown to be practical by its
implementation in a simulation.
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