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2014

Other Outputs

Learning to soar: exploration strategies in reinforcement learning for resource-constrained missions

Chung, Jen Jen (2014). Learning to soar: exploration strategies in reinforcement learning for resource-constrained missions. PhD Thesis, Faculty of Engineering and Information Technologies, School of Aerospace, Mechanical and Mechatronic Engineering, The University of Sydney.

Learning to soar: exploration strategies in reinforcement learning for resource-constrained missions

2013

Conference Publication

Gaussian processes for informative exploration in reinforcement learning

Chung, Jen Jen, Lawrance, Nicholas R.J. and Sukkarieh, Salah (2013). Gaussian processes for informative exploration in reinforcement learning. IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 6-10 May 2013. Washington, DC, United States: IEEE Computer Society. doi: 10.1109/icra.2013.6630938

Gaussian processes for informative exploration in reinforcement learning

2012

Conference Publication

A new utility function for smooth transition between exploration and exploitation of a wind energy field

Chung, Jen Jen, Angel, Miguel, Soto, Trujillo and Sukkarieh, Salah (2012). A new utility function for smooth transition between exploration and exploitation of a wind energy field. IEEE International Conference on Intelligent Robots and Systems, Vilamoura-Algarve, Portugal, 7-12 October 2012. Piscataway, NJ, United States: IEEE. doi: 10.1109/iros.2012.6385736

A new utility function for smooth transition between exploration and exploitation of a wind energy field

2011

Conference Publication

First airborne trial of a UAV based optical locust tracker

Brooker, Graham, Randle, Jeremy, Attia, Muhammad Esa, Xu, Zhe, Abuhashim, Tariq, Kassir, Abdallah, Chung, Jen Jen, Sukkarieh, Salah, Tahir, Nazifa and Dickens, John (2011). First airborne trial of a UAV based optical locust tracker. 2011 Australasian Conference on Robotics and Automation, Melbourne, VIC, Australia, 7-9 December 2011.

First airborne trial of a UAV based optical locust tracker