Reinforcement Learning

Documentation for package ‘reinforcelearn’ version 0.2.1

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