Research map / Reinforcement learning / MDPs and planning
Efficient Average Reward Reinforcement Learning Using Constant Shifting Values
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use constant shifting value from prior knowledge instead of adaptive shifting (CSV-learning vs R-learning) | R-learning · 4-circle MDP | mean total regret (x10^4): 7.5721 -> 0.9730 | Helped |
| CSV-learning vs PSRL | PSRL · 4-circle MDP | mean total regret (x10^4): 9.8138 -> 0.9730 | Helped |
| CSV-learning vs PSRL | PSRL · RiverSwim | mean total regret (x10^3): 0.0530 -> 0.0477 | Helped |
| CSV-learning vs PSRL | PSRL · 4-circle MDP | runtime (s): 13.31 -> 4.74 | Helped |
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