Research map / Multi-agent systems and games / Cooperative multi-agent RL
A Variational Perturbative Approach to Planning in Graph-Based Markov Decision Processes
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use VPT instead of API for disease control | GMDP planning · Disease control | relative deviation d_r [%]: 0 -> 0 | No clear effect |
| Use VPT instead of API for forest management | GMDP planning · Forest management | relative deviation d_r [%]: 1 -> 0 (μ,ν)=(0.3,0.3); 11 -> 1 (μ,ν)=(0.6,0.6); 38 -> 10 (μ,ν)=(0.9,0.9) | Helped |
| Use VPT instead of API for opinion dynamics | GMDP planning · Opinion dynamics | 95% deviation interval: 5.2 -> 0.8 (μ,ν)=(0.0,0.1); 5.7 -> 1.8 (μ,ν)=(0.1,0.1); 4.7 -> 0.0 (μ,ν)=(0.2,0.2) | Helped |
| Increase policy determinism (higher β) | VPT approximate inference · Random reward functions on tree and bidirectional-chain topologies | approximation accuracy | Hurt |
| Use a bidirectional chain rather than a tree topology | VPT approximate inference · Random reward functions | approximation accuracy | Hurt |
| Use VPT rather than mean-field policy in the synchronization task | 5×5 grid · Agent synchronization | mean order parameter over time | Helped |
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