Statements (57)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:software_framework
|
| gptkbp:applies_to |
multi-agent systems
stochastic environments |
| gptkbp:can_be_extended_by |
actor-critic methods
|
| gptkbp:can_be_used_with |
baseline methods
|
| gptkbp:developed_by |
gptkb:Richard_S._Sutton
|
| https://www.w3.org/2000/01/rdf-schema#label |
REINFORCE algorithm
|
| gptkbp:is |
simple to implement
used in finance used in robotics used in healthcare used in natural language processing model-free used in recommendation systems used in deep reinforcement learning based on the principle of temporal difference learning a benchmark for new algorithms a foundational algorithm in reinforcement learning a foundational concept in machine learning a key algorithm in deep learning a method for continuous action spaces a method for discrete action spaces a method for handling delayed rewards a method for handling sparse rewards a method for learning policies directly a method for learning value functions indirectly a method for optimizing long-term rewards a method for policy optimization a popular choice for research a stochastic policy optimization method a type of actor-critic method not suitable for large state spaces on-policy related to Q-learning related to SARSA suitable for discrete action spaces used in autonomous driving used in game playing used in offline learning used in online learning used in simulation-based optimization a part of the broader field of artificial intelligence |
| gptkbp:is_affected_by |
high variance
|
| gptkbp:is_enhanced_by |
variance reduction techniques
|
| gptkbp:is_evaluated_by |
return
|
| gptkbp:is_implemented_in |
gptkb:Graphics_Processing_Unit
gptkb:Library gptkb:Py_Torch |
| gptkbp:is_optimized_for |
expected reward
|
| gptkbp:is_used_for |
training agents
solve Markov decision processes |
| gptkbp:requires |
reward signal
Monte Carlo sampling |
| gptkbp:updates |
policy parameters
|
| gptkbp:used_in |
policy gradient methods
|
| gptkbp:bfsParent |
gptkb:A3_C
|
| gptkbp:bfsLayer |
5
|