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Evolutionary robotics: what, why, and where to
Evolutionary robotics applies the selection, variation, and heredity principles of natural
evolution to the design of robots with embodied intelligence. It can be considered as a …
evolution to the design of robots with embodied intelligence. It can be considered as a …
Neural modularity helps organisms evolve to learn new skills without forgetting old skills
A long-standing goal in artificial intelligence is creating agents that can learn a variety of
different skills for different problems. In the artificial intelligence subfield of neural networks …
different skills for different problems. In the artificial intelligence subfield of neural networks …
Diffusion-based neuromodulation can eliminate catastrophic forgetting in simple neural networks
A long-term goal of AI is to produce agents that can learn a diversity of skills throughout their
lifetimes and continuously improve those skills via experience. A longstanding obstacle …
lifetimes and continuously improve those skills via experience. A longstanding obstacle …
Artificial neurogenesis: An introduction and selective review
In this introduction and review—like in the book which follows—we explore the hypothesis
that adaptive growth is a means of producing brain-like machines. The emulation of neural …
that adaptive growth is a means of producing brain-like machines. The emulation of neural …
Investigating the evolution of a neuroplasticity network for learning
The processes of evolution and learning interact. Learning is an evolved strategy that
improves fitness, especially in a world where some aspects cannot realistically be encoded …
improves fitness, especially in a world where some aspects cannot realistically be encoded …
On the relationships between generative encodings, regularity, and learning abilities when evolving plastic artificial neural networks
A major goal of bio-inspired artificial intelligence is to design artificial neural networks with
abilities that resemble those of animal nervous systems. It is commonly believed that two …
abilities that resemble those of animal nervous systems. It is commonly believed that two …
Artificial evolution of plastic neural networks: a few key concepts
This chapter introduces a hierarchy of concepts to classify the goals and the methods used
in articles that mix neuro-evolution and synaptic plasticity. We propose definitions of …
in articles that mix neuro-evolution and synaptic plasticity. We propose definitions of …
Overcoming deception in evolution of cognitive behaviors
When scaling neuroevolution to complex behaviors, cognitive capabilities such as learning,
communication, and memory become increasingly important. However, successfully …
communication, and memory become increasingly important. However, successfully …
Evolving autonomous learning in cognitive networks
There are two common approaches for optimizing the performance of a machine: genetic
algorithms and machine learning. A genetic algorithm is applied over many generations …
algorithms and machine learning. A genetic algorithm is applied over many generations …
The evolution of a generalized neural learning rule
Evolution is extremely creative. The mere availability of a mechanism for synaptic change
seems to be enough for evolution to derive a learning rule. Many simulations of evolution …
seems to be enough for evolution to derive a learning rule. Many simulations of evolution …