International workshop on evolutionary and reinforcement learning for autonomous robot systems (ERLARS)

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Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks (2017, methodology): “The results showed that when neuromodulation is enabled, learning is evolved faster than when neuromodulation is not enabled, also with multi-robot distributed systems (Silva et al., 2012b).”
An Overview of Natural Language State Representation for Reinforcement Learning (2020, methodology): “Jonschkowski & Brock (2013) summarized other desirable properties of state representations proposed by many authors: It should provide good features for learning the value function; be compact but still allowing the original observations to be reconstructed; ar X iv :2 00 7.”