Deep Surrogate Assisted Generation of Environments. (arXiv:2206.04199v2 [cs.AI] UPDATED)

Recent progress in reinforcement learning (RL) has started producing
generally capable agents that can solve a distribution of complex environments.
These agents are typically tested on fixed, human-authored environments. On the
other hand, quality diversity (QD) optimization has been proven to be an
effective component of environment generation algorithms, which can generate
collections of high-quality environments that are diverse in the resulting
agent behaviors. However, these algorithms require potentially expensive
simulations of agents on newly generated environments. We propose Deep …

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