Anton Bernatskiy

Orcid: 0000-0002-7624-1615

According to our database1, Anton Bernatskiy authored at least 13 papers between 2014 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2018
Evolving morphology automatically reformulates the problem of designing modular control.
Adapt. Behav., 2018

2017
Reducing Training Environments in Evolutionary Robotics Through Ecological Modularity.
Proceedings of the Biomimetic and Biohybrid Systems - 6th International Conference, 2017

Simulating the evolution of soft and rigid-body robots.
Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Ecological modularity as a means to reduce necessary training environments in evolutionary robotics.
Proceedings of the Genetic and Evolutionary Computation Conference, 2017

Choice of robot morphology can prohibit modular control and disrupt evolution.
Proceedings of the Fourteenth European Conference Artificial Life, 2017

2016
Modularity and Sparsity: Evolution of Neural Net Controllers in Physically Embodied Robots.
Frontiers Robotics AI, 2016

Morphological Modularity Can Enable the Evolution of Robot Behavior to Scale Linearly with the Number of Environmental Features.
Frontiers Robotics AI, 2016

Exact rule-based stochastic simulations for the system with unlimited number of molecular species.
CoRR, 2016

Recombination Hotspots Promote the Evolvability of Modular Systems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2016

Embodiment Effects in Evolutionary Robotics.
Proceedings of the 38th Annual Meeting of the Cognitive Science Society, 2016

2015
Evolving Robot Morphology Facilitates the Evolution of Neural Modularity and Evolvability.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

Exploiting the Relationship Between Structural Modularity and Sparsity for Faster Network Evolution.
Proceedings of the Genetic and Evolutionary Computation Conference, 2015

2014
Improving Robot Behavior Optimization by Combining User Preferences.
Proceedings of the Fourteenth International Conference on the Simulation and Synthesis of Living Systems, 2014


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