FAPE: a Constraint-based Planner for Generative and Hierarchical Temporal Planning

1 code implementation • 25 Oct 2020 • Arthur Bit-Monnot, Malik Ghallab, Félix Ingrand, David E. Smith

FAPE's representation coherently integrates flexible timelines with hierarchical refinement methods that can provide efficient control knowledge.

Deliberative Acting, Online Planning and Learning with Hierarchical Operational Models

no code implementations • 2 Oct 2020 • Sunandita Patra, James Mason, Malik Ghallab, Dana Nau, Paolo Traverso

However, executing the planned actions has needed operational models, in which rich computational control structures and closed-loop online decision-making are used to specify how to perform an action in a nondeterministic execution context, react to events and adapt to an unfolding situation.

Decision Making Descriptive

Integrating Acting, Planning and Learning in Hierarchical Operational Models

no code implementations • 9 Mar 2020 • Sunandita Patra, James Mason, Amit Kumar, Malik Ghallab, Paolo Traverso, Dana Nau

We present new planning and learning algorithms for RAE, the Refinement Acting Engine.