rdgreene sa_tsp issues - Githubissues

rdgreene / sa_tsp

Q-Learning applied to the classic Travelling Salesman Problem

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Package functions in one script

#24 rdgreene closed 7 years ago
3
Repeat experiments with a more complex problem

#23 miguelesteras opened 7 years ago
3
Add functionality for softmax state transition policy

#22 miguelesteras opened 7 years ago
0
Implement 'n-step' Temporal Difference

#21 miguelesteras opened 7 years ago
0
Implement 'double' Q-Learning

#20 miguelesteras opened 7 years ago
0
Get Results: Q-Learning with 'default' parameters

#19 miguelesteras closed 7 years ago
0
Get Results: Q-Learning with different learning rates (alphas)

#18 miguelesteras closed 7 years ago
0
Get Results: Q-Learning with different epsilon / epsilon-decay values

#17 miguelesteras closed 7 years ago
0
Get Results: Q-Learning with different gamma values

#16 miguelesteras closed 7 years ago
0
Repeat the experiment in with different

#15 miguelesteras opened 7 years ago
0
Repeat the experiment in with different

#14 miguelesteras opened 7 years ago
0
Repeat the experiment in with different

#13 miguelesteras opened 7 years ago
0
Repeat the experiment in with different gamma values

#12 miguelesteras opened 7 years ago
0
Set the original R-matrix

#11 miguelesteras closed 7 years ago
2
Represent performance vs. episodes

#10 miguelesteras opened 7 years ago
0
Set the parameter values for Q-learning

#9 miguelesteras opened 7 years ago
2
Choose a policy

#8 miguelesteras closed 7 years ago
1
Define the reward function

#7 miguelesteras closed 7 years ago
1
Represent the problem with a graph

#6 miguelesteras closed 7 years ago
2
Set the original Q-matrix and show how it is updated in a learning episode

#5 miguelesteras opened 7 years ago
2
Define a state transition function

#4 rdgreene closed 7 years ago
4
Define domain & task

#3 rdgreene closed 7 years ago
1
Miguel work in progress

#2 miguelesteras closed 7 years ago
2
Review tsp.py and add code to plot results of parameter sweep

#1 rdgreene opened 7 years ago
4