  We consider the problem of optimal reactive synthesis - compute a strategy
that satisfies a mission specification in a dynamic environment, and optimizes
a performance metric. We incorporate task-critical information, that is only
available at runtime, into the strategy synthesis in order to improve
performance. Existing approaches to utilising such time-varying information
require online re-synthesis, which is not computationally feasible in real-time
applications. In this paper, we pre-synthesize a set of strategies
corresponding to candidate instantiations (pre-specified representative
information scenarios). We then propose a novel switching mechanism to
dynamically switch between the strategies at runtime while guaranteeing all
safety and liveness goals are met. We also characterize bounds on the
performance suboptimality. We demonstrate our approach on two examples -
robotic motion planning where the likelihood of the position of the robot's
goal is updated in real-time, and an air traffic management problem for urban
air mobility.
