The agent observes state, follows a policy, and receives consequences that may arrive after several steps. Learning estimates which actions improve expected cumulative reward while balancing exploration and exploitation.
Reinforcement learning trains an agent to choose actions using rewards received through interaction with an environment.
The agent observes state, follows a policy, and receives consequences that may arrive after several steps. Learning estimates which actions improve expected cumulative reward while balancing exploration and exploitation.