policy

Variable which encodes the behavior of the agent. This can be
either a <code>matrix</code>, <code>data.frame</code> or an <code><a rd-options="" href="/link/rl?package=ReinforcementLearning&version=1.0.2" data-mini-rdoc="ReinforcementLearning::rl">rl</a></code> object.

Calculates reinforcement learning policy from a given state-action table Q.
The policy is the decision-making function of the agent and defines the learning
agent's behavior at a given time.

Performs model-free reinforcement learning in R. This implementation enables the learning
of an optimal policy based on sample sequences consisting of states, actions and rewards. In
addition, it supplies multiple predefined reinforcement learning algorithms, such as experience
replay.

Nicolas Proellochs

ReinforcementLearning

Model-Free Reinforcement Learning

Stefan Feuerriegel

policy function

Variable which encodes the behavior of the agent. This can be
either a <code>matrix</code>, <code>data.frame</code> or an <code><a rd-options='' href='rl'>rl</a></code> object.

policy: Calculates the reinforcement learning policy

Description

Usage

Arguments

Value

See Also