10 datasets found

The dataset used in the paper is a set of waypoints and edges for planning.

The dataset used in this paper is a set of small SSP instances with small object counts, used to learn Generalized Policy Automata (GPAs) for solving larger related SSPs.

The dataset is used to test the generalized planning algorithm. It consists of a set of problems that share a common structure and can be solved by a single policy.

The dataset used in the paper is a collection of planning problems for classical and multi-agent epistemic planning.

The dataset used in the paper is a simulated dataset for scene understanding and planning tasks, containing images of objects and scenes.

The dataset is used for classical planning as QBF without grounding. It contains 20 domains from previous IPC competitions.

The dataset is used for classical planning as QBF without grounding. It contains 4 Organic Synthesis domains: OS-Sat18, OS-Opt18, Alkene, and MitExams.

A new approach to learning for planning, where knowledge acquired while solving a given set of planning problems is used to plan faster in related, but new problem instances.

A self-driving car dataset that captures real-world urban driving in the center of Las Vegas.

The dataset used in the paper is a Markov decision process (MDP) model of a robotic mission plan, which includes a set of states, actions, transitions, and labels.