smartgrid.rewards

This package contains various reward functions, used to compute a reward signal for each agent, based on their action and the resulting state of the environment.

Reward functions indicate to which degree the agent’s actions were appropriate, or in this case, ethical. By ethical, we mean that they are aligned with one or several moral values. These moral values are encoded in the reward function itself, which guides the learning of agents.

Traditionally, reward functions in the Reinforcement Learning literature are purely numerical, i.e., based on mathematical expressions. Such functions can be found in the smartgrid.rewards.numeric package.

Other functions can also be based on symbolic reasoning, such as argumentation: see the smartgrid.rewards.argumentation package.

members:

Modules

argumentation	Argumentation-based reward functions.
numeric	Numeric reward functions are purely based on mathematical expressions.
reward	The Reward abstract class defines a common (standard) API for reward functions.
reward_collection	The RewardCollection is responsible for computing rewards from reward functions.
reward_constraints	RewardConstraints allow to activate a reward function only when certain conditions are met.