dm_control: DeepMind Infrastructure for Physics-Based Simulation DeepMind的软件堆栈,用于基于物理的模拟和强化学习环境,使用MuJoCo物理。 1、基准任务 fromdm_controlimportsuiteimportnumpy as np domain_name='walker'task_name='walk'env=suite.load(domain_name, task_name) action_spec=env.action_spec() time...
Bottom: humanoid, manipulator, pendulum, point-mass, reacher, swimmer, walker. See the video overview. Download: Download full-size image Fig. 2. Procedural domains built with the PyMJCF and Composer task-authoring libraries. Left: Multi-legged creatures from the interactive tutorial. Middle: The...
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo. - google-deepmind/dm_control
to run SVEA on the default task,walker_walk. This should give you an output of the form: Working directory: logs/walker_walk/svea/0 Evaluating: logs/walker_walk/svea/0 | eval | S: 0 | ER: 26.2285 | ERTEST: 25.3730 | train | E: 1 | S: 250 | D: 70.1 s | R: 0.0000 | A...
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