Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 

Count-based Exploration with the Successor Representation

These are the commands we used to obtain the results reported in the Count-based Exploration with the Successor Representation. For the function approximation case the rom name should be adapted for different games, of course. This assumes one has the Arcade Learning Environment properly installed in their computer, as well as the other dependencies.

Tabular case:

python3 tabular_mbrl.py --input mdps/riverswim.mdp --num_episodes 100 --beta=100 --gamma 0.95 --epsilon 0.0 --seed 1

python3 tabular_mbrl.py --input mdps/sixarms.mdp --num_episodes 100 --beta=100 --gamma 0.95 --epsilon 0.0 --seed 1

python3 tabular_sarsa_sr.py --input mdps/riverswim.mdp --num_episodes 100 --beta 10000 --gamma 0.95 --epsilon 0.01 --seed 1 --step_size 0.1 --step_size_sr 0.5 --gamma_sr 0.5

python3 tabular_sarsa_sr.py --input mdps/sixarms.mdp --num_episodes 100 --beta 10000 --gamma 0.95 --epsilon 0.01 --seed 1 --step_size 0.5 --step_size_sr 0.25 --gamma_sr 0.5

python3 tabular_sarsa.py --input mdps/riverswim.mdp --num_episodes 100 --gamma 0.95 --epsilon 0.12 --seed 1 --step_size 0.37

python3 tabular_sarsa.py --input mdps/sixarms.mdp --num_episodes 100 --gamma 0.95 --epsilon 0.01 --seed 1 --step_size 0.43

Function Approximation case:

python3 -m exp_eig_sr.train --rom ../roms/montezuma_revenge.bin

About

No description, website, or topics provided.

Resources

License

Releases

No releases published

Packages

No packages published

Languages