Frozen Lake-v1

GPTKB entity

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