Man pages for jdtrat/rlsims
Simulate Reinforcement Learning Agents in R

check_action_reinforcement_episodes	Check Action/Reinforcement Episodes
check_arm_input	Check Arm Input
check_array_list_input	Have Input Checks for Setting Array Inputs
rl_action_simulate	Simulate an RL Agent's Action
rl_action_simulate.epsilonGreedy	Simulate an Action with a 'Epsilon-Greedy' Choice Policy
rl_action_simulate.greedy	Simulate an Action with a 'Greedy' Choice Policy
rl_action_simulate.softmax	Simulate an Action with a 'Softmax' Choice Policy
rl_arms_get_outcome	Get Arm's Outcome based on its Probability and Reward...
rl_define_arms	Define the Arm Structure
rl_define_array_factory	Factory for Defining Array Setting Functions
rl_define_new_agent	Define a New RL Agent
rl_define_policy	Define the Action-Selection Policy for an RL Agent
rl_define_reinforcements_array	Define Reinforcements Array for Tracking Cues in RL Agent's...
rl_define_stimuli_array	Define Cue Array for Tracking Cues in RL Agent's Environment
rl_policy_check_internal	Check Action-Selection Policy
rl_set_policy_internal	Generate Policy List
use_agent_template	Use an RL Agent Template from rlsims Package
zeros	Create a zero matrix.