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Found 9 papers, 3 papers with code
Lamarckian Inheritance Improves Robot Evolution in Dynamic Environments
This study explores the integration of Lamarckian system into evolutionary robotics (ER), comparing it with the traditional Darwinian model across various environments.
A comparison of controller architectures and learning mechanisms for arbitrary robot morphologies
The main question this paper addresses is: What combination of a robot controller and a learning method should be used, if the morphology of the learning robot is not known in advance?
Lamarck's Revenge: Inheritance of Learned Traits Can Make Robot Evolution Better
We research this issue through simulations with an evolutionary robot framework where morphologies (bodies) and controllers (brains) of robots are evolvable and robots also can improve their controllers through learning during their lifetime.
The Effects of Learning in Morphologically Evolving Robot Systems
Simultaneously evolving morphologies (bodies) and controllers (brains) of robots can cause a mismatch between the inherited body and brain in the offspring.
Gait-learning with morphologically evolving robots generated by L-system
The second approach is evolution plus learning which means the brain of a child is inherited as well, but additionally is developed by a learning algorithm - RevDEknn.
Morpho-evolution with learning using a controller archive as an inheritance mechanism
This causes a potential mismatch between the structure of an inherited controller and the new body.
Population-based Optimization for Kinetic Parameter Identification in Glycolytic Pathway in Saccharomyces cerevisiae
Models in systems biology are mathematical descriptions of biological processes that are used to answer questions and gain a better understanding of biological phenomena.
Differential Evolution with Reversible Linear Transformations
Differential evolution (DE) is a well-known type of evolutionary algorithms (EA).
Evolving embodied intelligence from materials to machines
Natural lifeforms specialise to their environmental niches across many levels; from low-level features such as DNA and proteins, through to higher-level artefacts including eyes, limbs, and overarching body plans.
