Mark Edgington

According to our database, Mark Edgington authored at least 15 papers between 2006 and 2016.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2016

Learning and Using Multimodal Stochastic Models: A Unified Approach.

Mark Edgington

PhD thesis, 2016

2015

Robotics echolocation test platform.

Xiaodong Wu, Palmer D'Orazio, Mark Edgington, Miguel Abrahantes

Proceedings of the IEEE International Conference on Electro/Information Technology, 2015

2009

Dynamic motion modelling for legged robots.

Mark Edgington, Yohannes Kassahun, Frank Kirchner

Proceedings of the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009

Learning complex robot control using evolutionary behavior based systems.

Yohannes Kassahun, Jakob Schwendner, Jose de Gea, Mark Edgington, Frank Kirchner

Proceedings of the Genetic and Evolutionary Computation Conference, 2009

2008

Learning Walking Patterns for Kinematically Complex Robots Using Evolution Strategies.

Malte Römmermann, Mark Edgington, Jan Hendrik Metzen, Jose de Gea, Yohannes Kassahun, Frank Kirchner

Proceedings of the Parallel Problem Solving from Nature, 2008

Evolving Neural Networks for Online Reinforcement Learning.

Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, Frank Kirchner

Proceedings of the Parallel Problem Solving from Nature, 2008

EANT+KALMAN: An Efficient Reinforcement Learning Method for Continuous State Partially Observable Domains.

Yohannes Kassahun, Jose de Gea, Jan Hendrik Metzen, Mark Edgington, Frank Kirchner

Proceedings of the KI 2008: Advances in Artificial Intelligence, 2008

Towards efficient online reinforcement learning using neuroevolution.

Jan Hendrik Metzen, Frank Kirchner, Mark Edgington, Yohannes Kassahun

Proceedings of the Genetic and Evolutionary Computation Conference, 2008

Accelerating neuroevolutionary methods using a Kalman filter.

Yohannes Kassahun, Jose de Gea, Mark Edgington, Jan Hendrik Metzen, Frank Kirchner

Proceedings of the Genetic and Evolutionary Computation Conference, 2008

Analysis of an evolutionary reinforcement learning method in a multiagent domain.

Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, Frank Kirchner

Proceedings of the 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), 2008

2007

A General Framework for Encoding and Evolving Neural Networks.

Yohannes Kassahun, Jan Hendrik Metzen, Jose de Gea, Mark Edgington, Frank Kirchner

Proceedings of the KI 2007: Advances in Artificial Intelligence, 2007

Exploiting Sensorimotor Coordination for Learning to Recognize Objects.

Yohannes Kassahun, Mark Edgington, Jose de Gea, Frank Kirchner

Proceedings of the IJCAI 2007, 2007

Performance evaluation of EANT in the robocup keepaway benchmark.

Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, Frank Kirchner

Proceedings of the Sixth International Conference on Machine Learning and Applications, 2007

A common genetic encoding for both direct and indirect encodings of networks.

Yohannes Kassahun, Mark Edgington, Jan Hendrik Metzen, Gerald Sommer, Frank Kirchner

Proceedings of the Genetic and Evolutionary Computation Conference, 2007

2006

Towards a Multimodal Sensorimotor Coordination Based Object Recognition System.

Yohannes Kassahun, Mark Edgington, Jose de Gea, Frank Kirchner

Proceedings of the IEEE International Conference on Robotics and Biomimetics, 2006