igibson.reward_functions package¶
Submodules¶
igibson.reward_functions.collision_reward module¶
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class
igibson.reward_functions.collision_reward.CollisionReward(config)¶ Bases:
igibson.reward_functions.reward_function_base.BaseRewardFunctionCollision reward Penalize robot collision. Typically collision_reward_weight is negative.
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get_reward(task, env)¶ Reward is self.collision_reward_weight if there is collision in the last timestep
- Parameters
task – task instance
env – environment instance
- Returns
reward
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igibson.reward_functions.point_goal_reward module¶
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class
igibson.reward_functions.point_goal_reward.PointGoalReward(config)¶ Bases:
igibson.reward_functions.reward_function_base.BaseRewardFunctionPoint goal reward Success reward for reaching the goal with the robot’s base
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get_reward(task, env)¶ Check if the distance between the robot’s base and the goal is below the distance threshold
- Parameters
task – task instance
env – environment instance
- Returns
reward
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igibson.reward_functions.potential_reward module¶
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class
igibson.reward_functions.potential_reward.PotentialReward(config)¶ Bases:
igibson.reward_functions.reward_function_base.BaseRewardFunctionPotential reward Assume task has get_potential implemented; Low potential is preferred (e.g. a common potential for goal-directed task is the distance to goal)
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get_reward(task, env)¶ Reward is proportional to the potential difference between the current and previous timestep
- Parameters
task – task instance
env – environment instance
- Returns
reward
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reset(task, env)¶ Compute the initial potential after episode reset
- Parameters
task – task instance
env – environment instance
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igibson.reward_functions.reaching_goal_reward module¶
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class
igibson.reward_functions.reaching_goal_reward.ReachingGoalReward(config)¶ Bases:
igibson.reward_functions.reward_function_base.BaseRewardFunctionReaching goal reward Success reward for reaching the goal with the robot’s end-effector
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get_reward(task, env)¶ Check if the distance between the robot’s end-effector and the goal is below the distance threshold
- Parameters
task – task instance
env – environment instance
- Returns
reward
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igibson.reward_functions.reward_function_base module¶
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class
igibson.reward_functions.reward_function_base.BaseRewardFunction(config)¶ Bases:
objectBase RewardFunction class Reward-specific reset and get_reward methods are implemented in subclasses
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abstract
get_reward(task, env)¶ Compute the reward at the current timestep. Overwritten by subclasses.
- Parameters
task – task instance
env – environment instance
- Returns
reward, info
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reset(task, env)¶ Perform reward function-specific reset after episode reset. Overwritten by subclasses.
- Parameters
task – task instance
env – environment instance
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abstract