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Supporting multirollout for the simapp released as of reInvent 2019 (#…
…983)
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26 changes: 26 additions & 0 deletions
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reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/actions/default.json
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,26 @@ | ||
| { | ||
| "action_space": [ | ||
| { | ||
| "steering_angle": -30, | ||
| "speed": 0.6 | ||
| }, | ||
| { | ||
| "steering_angle": -15, | ||
| "speed": 0.6 | ||
| }, | ||
| { | ||
| "steering_angle": 0, | ||
| "speed": 0.6 | ||
| }, | ||
| { | ||
| "steering_angle": 15, | ||
| "speed": 0.6 | ||
| }, | ||
| { | ||
| "steering_angle": 30, | ||
| "speed": 0.6 | ||
| } | ||
| ], | ||
| "sensor": ["FRONT_FACING_CAMERA"], | ||
| "neural_network": "DEEP_CONVOLUTIONAL_NETWORK_SHALLOW" | ||
| } |
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...earning/rl_deepracer_robomaker_coach_gazebo/src/markov/agent_ctrl/agent_ctrl_interface.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,46 @@ | ||
| '''This class this defines an interface for how agents need to interact with the | ||
| environment, all concrete classes should abstract away the communication of the | ||
| agent with gazebo | ||
| ''' | ||
| import abc | ||
|
|
||
| class AgentCtrlInterface(object, metaclass=abc.ABCMeta): | ||
| @property | ||
| @abc.abstractmethod | ||
| def action_space(self): | ||
| '''Returns a read onlu version of the action space so that is can be passed to coach''' | ||
| raise NotImplementedError('Agent control must be able retrieve action space') | ||
|
|
||
| @abc.abstractmethod | ||
| def reset_agent(self): | ||
| '''Reset the agent to a desired start postion | ||
| ''' | ||
| raise NotImplementedError('Agent control must be able to reset agent') | ||
|
|
||
| @abc.abstractmethod | ||
| def send_action(self, action): | ||
| '''Send the desired action to the agent | ||
| action - Integer with the desired action to take | ||
| ''' | ||
| raise NotImplementedError('Agent control must be able to send action') | ||
|
|
||
| @abc.abstractmethod | ||
| def judge_action(self, action): | ||
| '''Returns the reward and done flag after and agent takes the action prescribed by a given | ||
| policy | ||
| action - Integer with the desired action to take | ||
| ''' | ||
| raise NotImplementedError('Agent control must be able to judge action') | ||
|
|
||
| @abc.abstractmethod | ||
| def finish_episode(self): | ||
| '''Runs all behavior required at the end of the episode, such as uploading | ||
| debug data to S3. | ||
| ''' | ||
| raise NotImplementedError('Agent control must be able to properly handle the end of \ | ||
| an episode') | ||
|
|
||
| @abc.abstractmethod | ||
| def clear_data(self): | ||
| '''Clears the agent data''' | ||
| raise NotImplementedError('Agent control must be able to clear data') |
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