  We develop a general framework for abstracting the behavior of an agent that
operates in a nondeterministic domain, i.e., where the agent does not control
the outcome of the nondeterministic actions, based on the nondeterministic
situation calculus and the ConGolog programming language. We assume that we
have both an abstract and a concrete nondeterministic basic action theory, and
a refinement mapping which specifies how abstract actions, decomposed into
agent actions and environment reactions, are implemented by concrete ConGolog
programs. This new setting supports strategic reasoning and strategy synthesis,
by allowing us to quantify separately on agent actions and environment
reactions. We show that if the agent has a (strong FOND) plan/strategy to
achieve a goal/complete a task at the abstract level, and it can always execute
the nondeterministic abstract actions to completion at the concrete level, then
there exists a refinement of it that is a (strong FOND) plan/strategy to
achieve the refinement of the goal/task at the concrete level.
