Statements (63)
Predicate | Object |
---|---|
gptkbp:instance_of |
gptkb:environment
|
gptkbp:analyzes |
simulation environments
heat maps grid representation |
gptkbp:challenges |
holes
|
gptkbp:difficulty_levels |
gptkb:medium
|
gptkbp:emulation |
gptkb:Python
gptkb:Jupyter_notebooks |
gptkbp:has_action_space |
finite action space
|
gptkbp:has_actions |
right
left down up |
gptkbp:has_discount_factor |
configurable
|
gptkbp:has_end_state |
goal position
|
gptkbp:has_goal |
reach the goal square
|
gptkbp:has_initial_state |
start at a random position
|
gptkbp:has_learning_rate |
configurable
|
gptkbp:has_membership |
frozen lake states
|
gptkbp:has_state_space |
finite state space
|
gptkbp:has_variations |
deterministic
stochastic |
https://www.w3.org/2000/01/rdf-schema#label |
Frozen Lake-v1
|
gptkbp:is_a_solution_for |
gptkb:Deep_Q-Networks
Q-learning SARSA |
gptkbp:is_compatible_with |
gptkb:Tensor_Flow
gptkb:Python_3 gptkb:Py_Torch |
gptkbp:is_designed_for |
grid world problems
|
gptkbp:is_documented_in |
Git Hub repositories
Open AI Gym documentation |
gptkbp:is_evaluated_by |
performance metrics
agent performance |
gptkbp:is_implemented_in |
Gym library
Open AI Gym library |
gptkbp:is_part_of |
gptkb:gymnasium
gptkb:Open_AI_Gym's_classic_control_suite AI competitions AI courses AI research projects AI tutorials reinforcement learning benchmarks |
gptkbp:is_popular_in |
gptkb:AI_technology
machine learning community |
gptkbp:is_simulated_with |
Markov Decision Processes
|
gptkbp:is_tested_for |
gptkb:students
AI researchers reinforcement learning algorithms AI agents |
gptkbp:is_used_for |
policy evaluation
algorithm comparison policy improvement training AI models reinforcement learning experiments |
gptkbp:is_used_in |
educational purposes
reinforcement learning robotics research |
gptkbp:length |
4x4 or 8x8 grid
|
gptkbp:prize_pool |
negative reward for falling into a hole
positive reward for reaching goal |
gptkbp:bfsParent |
gptkb:gymnasium
|
gptkbp:bfsLayer |
4
|