Aizaz.Sharif

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Aizaz Sharif

Affiliated PhD student

Organisation:

Department of Validation Intelligence for Autonomous Software Systems

Email:

[email protected]

Most recent publications

A. Sharif and D. Marijan

Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment

In 22nd IEEE International Conference on Software Quality, Reliability, and Security (QRS). 22nd International Conference on Software Quality, Reliability and Security (QRS): IEEE, 2022.

Proceedings, refereed

2022

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A. Sharif and D. Marijan

Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies

In 29th Asia-Pacific Software Engineering Conference (APSEC). 29th Asia-Pacific Software Engineering Conference (APSEC): IEEE, 2022.

Proceedings, refereed

2022

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Find publication

2022

Proceedings, refereed

A. Sharif and D. Marijan

Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment

In 22nd IEEE International Conference on Software Quality, Reliability, and Security (QRS). 22nd International Conference on Software Quality, Reliability and Security (QRS): IEEE, 2022.

Status: Published

A. Sharif and D. Marijan

Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies

In 29th Asia-Pacific Software Engineering Conference (APSEC). 29th Asia-Pacific Software Engineering Conference (APSEC): IEEE, 2022.

Status: Published

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Most recent publications

Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment

Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies

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Departments

Publication type

Year published

Proceedings, refereed

Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment

Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies

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Most recent publications

Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment

Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies

Find publication

Status

Departments

Publication type

Year published

Proceedings, refereed

Evaluating the Robustness of Deep Reinforcement Learning for Autonomous Policies in a Multi-agent Urban Driving Environment

Adversarial Deep Reinforcement Learning for Improving the Robustness of Multi-agent Autonomous Driving Policies