We consider the sequential composite binary hypothesis testing problem in which one of hypotheses is governed by a single distribution while other family distributions whose parameters belong to known set $\Gamma $ . would like design...

This paper studies optimal motion planning subject to and environment uncertainties. By modeling the system as a probabilistic labeled Markov decision process (PL-MDP), control objective is synthesize finite-memory policy, under which agent satisfies complex high-level tasks expressed linear temporal logic (LTL) with desired satisfaction probability. In particular, cost optimization of trajecto...

Previously proposed qualitative probabilities do not satisfy the requirements of temporal reasoning, and a new abstraction is proposed here that represents probability changes over time using four values: increasing, decreasing, constant, and unknown. The qualitative temporal probability presented satisfies the axioms of probability by obeying a set of probabilistic constraints. Temporal constr...