We argue that bidding in the game of Contract Bridge can profitably be
regarded as a micro-world suitable for experimenting with pragmatics. We sketch an
analysis in which a "bidding system" is treated as the semantics of an artificial
language, and show how this "language", despite its apparent simplicity, is capable of
supporting a wide variety of common speech acts parallel to those in natural languages;
we also argue that the reason for the relatively unsuccessful nature of previous
attempts to write strong Bridge playing programs has been their failure to address the
need to reason explicitly about knowledge, pragmatics, probabilities and plans. We give
an overview of Pragma, a system currently under development at SICS, which embodies
these ideas in concrete form, using a combination of rule-based inference, stochastic
simulation, and "neural-net" learning. Examples are given illustrating the functionality
of the system in its current form