In this paper we present an algorithm for planning in nondeterministic domains. Our algorithm C-SHOP extends the successful classical HTN planner SHOP, by introducing new mechanisms to handle situations where there is incomplete and uncertain information about the state of the environment. Being an HTN planner, C-SHOP supports coding domain-dependent knowledge in a powerful way that describes h...

This study examines the effects of age, cognitive resources, and task familiarity on planning performance. Fifty-two young and 52 old adults completed one of two errand-planning tasks. The tasks were matched for structure, difficulty, and format, but differed in content, such that one planning task required planning a real-world shopping tour whereas the other involved planning an unfamiliar sp...

We present a compilation-based approach to reducing the representational distance between application domain experts and AI planning technology. The approach combines a representation designed to match the structure of human expertise in the construction industry with an established planning technique. The design of this representation is derived from a study carried out with experts in the ind...

The Action Notation Modeling Language (ANML) provides a high-level, convenient, and succinct alternative to existing planning languages such as PDDL, the IxTeT language, and languages developed at NASA, such as the EUROPA modeling language (NDDL), and the ASPEN modeling language (AML). ANML is based on strong notions of action and state (like PDDL, IxTeT, and AML), uses a variable/value model (...

Planning in robotics is often split into task and motion planning. The high-level, symbolic task planner decides what needs to be done, while the motion planner checks feasibility and fills up geometric detail. It is known however that such a decomposition is not effective in general as the symbolic and geometrical components are not independent. In this work, we show that it is possible to com...

We present a compilation-based approach to reducing the representational distance between application domain experts and AI planning technology. The approach combines a representation designed to match the structure of human expertise in the construction industry with an established planning technique. The design of this representation is derived from a study carried out with experts in the ind...

Among the underwater robotic systems that are currently available, remotely operated vehicles (ROVs) are the most commonly used underwater robotic systems. A ROV is an underwater vehicle that is controlled from a mother-ship by human operators. Sometimes a ROV is equipped with one or more robotic manipulators to perform underwater tasks. These robotic manipulators are also controlled by human o...

We present a compilation-based approach that combines a formalism designed to match the structure of human expertise in the construction industry with an established planning technique. The domain's modelling requirements are derived from a study carried out with domain experts. This study shows that expertise in the industry is centred on the components of a building organised into a subcompon...