Unavoidable dead-ends are common in many probabilistic planning problems, eg when
actions may fail or when operating under resource constraints. An important objective in …

Planning is motivated by acting. Most of the existing work on automated planning
underestimates the reasoning and deliberation needed for acting; it is instead biased …

This paper explores the execution of planned autonomous underwater vehicle (AUV)
missions where opportunities to achieve additional utility can arise during execution. The …

Рассматриваются вопросы разработки эффективных инструментальных средств для
построения интеллектуальных систем, в частности, интегрированных экспертных …

Maximizing goal probability is an important objective in probabilistic planning, yet algorithms
for its optimal solution are severely underexplored. There is scant evidence of what the …

This work is focused on the topical problem of developing efficient software tools to design
intelligent systems, in particular, integrated expert systems (IESs), which have powerful …

Рассматриваются проблемы интеллектуализации процессов разработки
интегрированных экспертных систем на основе задачно-ориентированной …

Traditionally, planning provides for execution plans as sequences of actions with
preconditions and effects. Execution monitoring identifies failure conditions when the …

Intelligent robots need to generate and execute plans. In order to deal with the complexity of
real environments, planning makes some assumptions about the world. When executing …

In real-world applications, the ability to reason about incomplete knowledge, sensing,
temporal notions, and numeric constraints is vital. While several AI planners are capable of …