@skyfallai: Why do we need a Big World Environment for Continual Learning? Simply because currently RL benchmarks such as Atari, Op…
Summary
The article argues that current RL benchmarks are episodic, stationary, and non-persistent, failing to reflect real-world continual learning, and introduces the Morpheus big world environment to address these issues.
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Why do we need a Big World Environment for Continual Learning?
Simply because currently RL benchmarks such as Atari, OpenAI Gym, MuJoCo, and Procgen share the below three properties that have nothing to do with the real world and will never help reach Continual Learning.
Episodic: every task ends and the world resets to a clean state Stationary: the rules and dynamic of the environment stay the same Non-persistent: past decisions don’t affect future ones. A failed episode carries no consequence into the next one.
In the real world, the environment never resets and it constantly evolves causing humans to continually adjust and adapt to new environments. This is why we need a Big World environment like Morpheus.
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