spriteworld - Spriteworld: a flexible, configurable python-based reinforcement learning environment

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Spriteworld is a python-based RL environment that consists of a 2-dimensional arena with simple shapes that can be moved freely. This environment was developed for the COBRA agent introduced in the paper "COBRA: Data-Efficient Model-Based RL through Unsupervised Object Discovery and Curiosity-Driven Exploration" (Watters et al., 2019). The motivation for the environment was to provide as much flexibility for procedurally generating multi-object scenes while retaining as simple an interface as possible. Spriteworld sprites come in a variety of shapes and can vary continuously in position, size, color, angle, and velocity. The environment has occlusion but no physics, so by default sprites pass beneath each other but do not collide or interact in any way. Interactions may be introduced through the action space, which can update all sprites each timestep. For example, the DiscreteEmbodied action space (see spriteworld/action_spaces.py) implements a rudimentary form of physics in which an agent's body sprite can adhere to and carry sprites underneath it.

https://github.com/deepmind/spriteworld

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