This paper introduces a concept of safe path planning for UAV's autonomous operation in an
urban environment where GNSS-positioning may become unreliable or even unavailable. If …

Sequential decision-making problems arise in every arena of daily life and pose unique
challenges for research in decision-theoretic planning. Although there has been a wide …

Aircraft routing problem is a crucial component for flight automation. Despite recent
successes, challenges still remain when the environment is dynamic and uncertain. In this …

Heuristic search is a powerful approach that has successfully been applied to a broad class
of planning problems, including classical planning, multi-objective planning, and …

Heuristic search algorithms for goal-probability maximization (MaxProb) have been known
since a decade. Yet prior work on heuristic functions for MaxProb relies on determinization …

Stochastic shortest-path problems (SSP) are an important subclass of MDPs for which
heuristic search algorithms exist since over a decade. Yet most known heuristic functions …

The merge-and-shrink framework is a powerful tool to construct state space abstractions
based on factored representations. One of its core applications in classical planning is the …

This paper looks at predictability problems, ie, wherein an agent must choose its strategy in
order to optimize the predictions that an external observer could make. We address these …

Stochastic shortest path problems (SSPs) capture probabilistic planning tasks with the
objective of minimizing expected cost until reaching the goal. One of the strongest methods …

The planning domain has experienced increased interest in the formal synthesis of decision-
making policies. This formal synthesis typically entails finding a policy which satisfies formal …