Sentence examples for task failure from inspiring English sources

A long-standing goal of AI is to enable robots to plan in the face of uncertain and incomplete information, and to handle task failure intelligently.

Contraction duration for the EMG task was fixed for each subject to the time to task failure of the torque task (104 ± 20 s).

Therefore, this paper makes an effort to focus on the research problem of designing an intelligent task failure prediction models for facilitating proactive fault tolerance by predicting task failures for Scientific Workflow applications.

By combining the knowledge layers with the models of knowledge effects, we can simultaneously solve several problems in robotics: (i) task planning and execution under uncertainty; (ii) task planning and execution in open worlds; (iii) explaining task failure; (iv) verifying those explanations.

There are three different failure modes, task failure, TaskTracker failure, and JobTracker failure.

Introduction Devices' ergonomics are major determinants of task failure, especially in stressful environments.

Then, the proposed failure models have also been validated using Pegasus and Amazon EC2 by comparing actual task failures with predicted task failures.

Overall, task failures are principally failures to provide adequate technical safety barriers and failures to operate provided barriers appropriately.

In such a context, a force overshoot may result in task failures (e.g., gripper losses the component, component damages), representing a critical control issue.

On the basis of investigation reports the incidents were entered in a tailor-made tool called Storybuilder developed for the Dutch Ministry of Social Affairs and Employment for identifying the dominant patterns of technical safety barrier failures, barrier task failures and underlying management causes associated with the resulting loss of control events.

To reduce the failure effect of workflow tasks on the Cloud resources during execution, task failures can be intelligently predicted by proactively analyzing the data of multiple scientific workflows using the state of the art of machine learning approaches for failure prediction.