FoPra Beluga Challenge - Reinforcement Learning
v1.0
Deep Reinforcement Learning solution for the Beluga Challenge shipping container optimization problem using PPO and MCTS
Here is a list of all namespace functions with links to the namespace documentation for each function:
check_deliver_to_hangar() :
rl.env.check_action
check_get_from_hangar() :
rl.env.check_action
check_left_stack_rack() :
rl.env.check_action
check_left_unstack_rack() :
rl.env.check_action
check_load_beluga() :
rl.env.check_action
check_right_stack_rack() :
rl.env.check_action
check_right_unstack_rack() :
rl.env.check_action
check_unload_beluga() :
rl.env.check_action
debuglog() :
rl.utils.utils
decide_parameters() :
rl.agents.low_level.heuristics
deliver_to_hangar() :
rl.env.action
extract_id() :
rl.env.state
filter_problem() :
rl.utils.problem_filter
generate_problems() :
rl.utils.problem_filter
get_from_hangar() :
rl.env.action
get_name_from_id() :
rl.env.state
get_type() :
rl.env.state
install_package() :
setup_dependencies
left_stack_rack() :
rl.env.action
left_unstack_rack() :
rl.env.action
load_beluga() :
rl.env.action
load_from_json() :
rl.env.state
main() :
rl.main
,
setup_dependencies
permute_high_level_observation() :
rl.utils.utils
right_stack_rack() :
rl.env.action
right_unstack_rack() :
rl.env.action
unload_beluga() :
rl.env.action
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