Vinod Valsalam
Ph.D. Student (Alumni)
Vinod's research focuses on understanding how learning and evolution interact in producing complex systems.
Using Symmetry and Evolutionary Search to Minimize Sorting Networks 2013
Vinod K. Valsalam and Risto Miikkulainen
Constructing Controllers for Physical Multilegged Robots using the ENSO Neuroevolution Approach 2012
Vinod K. Valsalam, Jonathan Hiller, Robert MacCurdy, Hod Lipson and Risto Miikkulainen
Evaluation Methods for Active Human-Guided Neuroevolution in Games 2012
Igor Karpov, Leif Johnson, Vinod Valsalam and Risto Miikkulainen
Assisting Machine Learning Through Shaping, Advice and Examples 2011
Igor Karpov, Vinod Valsalam and Risto Miikkulainen
Evolving Symmetry for Modular System Design 2011
Vinod K. Valsalam and Risto Miikkulainen
Human-Assisted Neuroevolution Through Shaping, Advice and Examples 2011
Igor V. Karpov, Vinod K. Valsalam and Risto Miikkulainen
Utilizing Symmetry and Evolutionary Search to Minimize Sorting Networks 2011
Vinod K. Valsalam and Risto Miikkulainen
Utilizing Symmetry in Evolutionary Design 2010
Vinod Valsalam
Evolving Symmetric and Modular Neural Network Controllers for Multilegged Robots 2009
Vinod K. Valsalam and Risto Miikkulainen
Evolving Symmetric and Modular Neural Networks for Distributed Control 2009
Vinod K. Valsalam and Risto Miikkulainen
Modular Neuroevolution for Multilegged Locomotion 2008
Vinod K. Valsalam and Risto Miikkulainen
Developing Complex Systems Using Evolved Pattern Generators 2007
Vinod K. Valsalam, James A. Bednar and Risto Miikkulainen
Establishing an Appropriate Learning Bias Through Development 2006
Vinod K. Valsalam, James A. Bednar, and Risto Miikkulainen
Constructing Good Learners Using Evolved Pattern Generators 2005
Vinod K. Valsalam, James A. Bednar, and Risto Miikkulainen
ENSO This package contains software implementing the ENSO approach for evolving symmetric modular neural networks. It also in... 2010

Sorting Networks This package contains software utilizing an approach based on symmetry and evolution to minimize the number of comparato... 2010