activity
20112022
most citedPDDL2.1: An Extension to PDDL for Expressing Temporal Planning Domains

1.7k citations · 2.9k across the 15 of their papers we have counts for

collaborators

16 papers

cs.RO2022

Autonomous Passage Planning for a Polar Vessel

Jonathan D. Smith, Samuel Hall, George Coombs +6

We introduce a method for long-distance maritime route planning in polar regions, taking into account complex changing environmental conditions. The method allows the construction…

cs.RO2021

Long-Range Route-planning for Autonomous Vehicles in the Polar Oceans

Maria Fox, Michael Meredith, J. Alexander Brearley +2

There is an increasing demand for piloted autonomous underwater vehicles (AUVs) to operate in polar ice conditions. At present, AUVs are deployed from ships and directly human-pilo…

cs.AI2021

Improving Search by Utilizing State Information in OPTIC Planners Compilation to LP

Elad Denenberg, Amanda Coles, Derek Long

Automated planners are computer tools that allow autonomous agents to make strategies and decisions by determining a set of actions for the agent that to take, which will carry a s…

cs.AI2021★ 1 cited

Efficient Temporal Piecewise-Linear Numeric Planning with Lazy Consistency Checking

Josef Bajada, Maria Fox, Derek Long

Temporal planning often involves numeric effects that are directly proportional to their action's duration. These include continuous effects, where a numeric variable is subjected…

cs.AI2021

D-VAL: An automatic functional equivalence validation tool for planning domain models

Anas Shrinah, Derek Long, Kerstin Eder

This paper introduces an approach to validate the functional equivalence of planning domain models. Validating the functional equivalence of planning domain models is the problem o…

cs.AI2021

Contrastive Explanations of Plans Through Model Restrictions

Benjamin Krarup, Senka Krivic, Daniele Magazzeni +3

In automated planning, the need for explanations arises when there is a mismatch between a proposed plan and the user's expectation. We frame Explainable AI Planning in the context…