Research map / Reinforcement learning / Policy gradient and actor-critic
Policy Gradient With Value Function Approximation For Collective Multiagent Planning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use neighborhood count observations (oN) instead of local-state-only observations (o0) (ablation) | Factored actor-critic · Taxi supply-demand matching, 8000 taxis | solution quality: 64% | Helped |
| Use neighborhood count observations (oN) instead of current-state count observations (o1) (ablation) | Factored actor-critic · Taxi supply-demand matching, 8000 taxis | solution quality: 20% | Helped |
| Use current-state count observations (o1) instead of local-state-only observations (o0) (ablation) | Factored actor-critic · Taxi supply-demand matching | solution quality | Helped |
| Use the factored actor and factored critic update (ablation) | Actor-critic · Taxi supply-demand matching, o0, o1, and oN | convergence | Helped |
| Use non-factored actor updates instead of the factored actor update (ablation) | Actor-critic · Taxi supply-demand matching, o0, o1, and oN | convergence | Hurt |
| Use non-factored critic updates instead of the factored critic update (ablation) | Actor-critic · Taxi supply-demand matching, o0, o1, and oN | convergence | Hurt |
| Train the critic with individual value-function targets rather than global empirical returns (ablation) | Actor-critic · Larger collective planning problems | convergence | Helped |
| Use count-dependent policies rather than policies based only on local state (ablation) | Factored actor-critic · Taxi supply-demand matching | solution quality | Helped |
| Use EM with a piecewise policy over neighborhood observations (ablation) | EM · Taxi supply-demand matching, oN | convergence: 30K iterations | Hurt |
| Use the factored actor-critic method instead of SMFU | Collective multiagent planning · Robot navigation in a congested environment, oN | solution quality | Helped |
| Use neighborhood count observations (oN) instead of less informative observation models (ablation) | Factored actor-critic · Robot navigation in a congested environment | solution quality | Helped |
Closest papers by meaning
- Credit Assignment For Collective Multiagent RL With Global Rewards (NeurIPS 2018 · similarity 0.89)
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- Multi-Agent Reinforcement Learning with General Utilities via Decentralized Shadow Reward Actor-Critic (AAAI 2022 · similarity 0.89)
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