  "Standard" information theory says nothing about the semantic content of
information. Nevertheless, applications such as evolutionary theory demand
consideration of precisely this aspect of information, a need that has
motivated a largely unsuccessful search for a suitable measure of an "amount of
meaning". This paper represents an attempt to move beyond this impasse, based
on the observation that the meaning of a message can only be understood
relative to its receiver. Positing that the semantic value of information is
its usefulness in making an informed decision, we define pragmatic information
as the information gain in the probability distributions of the receiver's
actions, both before and after receipt of a message in some pre-defined
ensemble. We then prove rigorously that our definition is the only one that
satisfies obvious desiderata, such as the additivity of information from
logically independent messages. This definition, when applied to the
information "learned" by the time evolution of a process, defies the intuitions
of the few previous researchers thinking along these lines by being monotonic
in the uncertainty that remains after receipt of the message, but non-monotonic
in the Shannon entropy of the input ensemble. It then follows that the
pragmatic information of the genetic "messages" in an evolving population is a
global Lyapunov function for Eigen's quasi-species model of biological
evolution. A concluding section argues that a theory such as ours must
explicitly acknowledge purposeful action, or "agency", in such diverse fields
as evolutionary theory and finance.
