Autonomous robots are increasingly served in real-world unstructured human environments
with complex long-horizon tasks, such as restaurant serving and office delivery. Task and …

Hierarchies are one of the most common structures used to understand and conceptualise
the world. Within the field of Artificial Intelligence (AI) planning, which deals with the …

Automated machine learning (AutoML) is a young research area aiming at making high-
performance machine learning techniques accessible to a broad set of users. This is …

Comparing different AutoML frameworks is notoriously challenging and often done
incorrectly. We introduce an open and extensible benchmark that follows best practices and …

Automated machine learning (AutoML) seeks to automatically select, compose, and
parametrize machine learning algorithms, so as to achieve optimal performance on a given …

The key to utilizing the potential of multirobot systems is cooperation. How can we achieve
cooperation in systems composed of failure-prone autonomous robots operating in noisy …

Automation does not mean humans are replaced; quite the opposite. Increasingly, humans
are asked to interact with automation in complex and typically large-scale systems, including …

In order to cope with the task allocation in national economic mobilization, a task allocation
planning method based on Hierarchical Task Network (HTN) for national economic …

SHOP (Simple Hierarchical Ordered Planner) is a domain-independent HTN planning
system with the following characteristics.• SHOP plans for tasks in the same order that they …

Objective: To develop a method enabling human-like, flexible supervisory control via
delegation to automation. Background: Real-time supervisory relationships with automation …