# Reinforcement Learning

## Documentation for package ‘reinforcelearn’ version 0.2.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

reinforcelearn-package | Reinforcement Learning.
cliff.walking | Cliff Walking
CliffWalking | Cliff Walking
Eligibility | Eligibility traces
eligibility | Eligibility traces
Environment | Custom Reinforcement Learning Environment
EpsilonGreedyPolicy | Epsilon Greedy Policy
experience.replay, | Experience Replay
getEligibilityTraces | Get eligibility traces
getReplayMemory | Get replay memory.
getStateValues | Get state values.
getValueFunction | Get weights of value function.
GreedyPolicy | Epsilon Greedy Policy
Gridworld | Gridworld
GymEnvironment | Gym Environment
iht | Tile Coding
interact | Interaction between agent and environment.
makeAgent | Create Agent.
makeAlgorithm | Make reinforcement learning algorithm.
makeEnvironment | Create reinforcement learning environment.
makePolicy | Create policy.
makeReplayMemory | Experience Replay
makeValueFunction | Value Function Representation
MdpEnvironment | MDP Environment
mountain.car | Mountain Car
MountainCar | Mountain Car
MountainCarContinuous | Mountain Car
MountainCarContinuous, | Mountain Car
neural.network | Value Network
nHot | Make n hot vector.
Policy | Create policy.
QLearning | Q-Learning
qlearning | Q-Learning
RandomPolicy | Random Policy
reinforcelearn | Reinforcement Learning.
reinforcementlearning | Reinforcement Learning.
replay.memory | Experience Replay
SoftmaxPolicy | Softmax Policy
table | Value Table
tiles | Tile Coding
ValueNetwork | Value Network
ValueTable | Value Table
windy.gridworld | Windy Gridworld
WindyGridworld | Windy Gridworld