Research map / Reinforcement learning / MDPs and planning
Communicating via Markov Decision Processes
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use MEME instead of RL+PR | CodeGrid · CodeGrid (64 and 128 messages) | message accuracy | Helped |
| Use MEME instead of RL+PR | CodeGrid · CodeGrid (128 messages) | message accuracy | Helped |
| Increase the message space from 32 to 128 messages | RL+PR · CodeGrid | message accuracy | Hurt |
| Use MEME to couple the message posterior with the MaxEnt policy | CodeCart · CodeCart (no actuator noise) | pixel error | Helped |
| Use MEME to couple the message posterior with the MaxEnt policy | CodePong · CodePong (no actuator noise) | pixel error | Helped |
| Add actuator noise | MEME on CodeCart · CodeCart | pixel error | Hurt |
| Add actuator noise | MEME on CodeCart · CodeCart | MDP return | No clear effect |
| Add actuator noise | MEME on CodePong · CodePong | MDP return | Hurt |
| Add actuator noise | MEME on CodePong · CodePong | pixel error | No clear effect |
| Increase actuator noise up to p=1/2 | MEME on CodeCart and CodePong · CodeCart and CodePong | performance | Hurt |
Closest papers by meaning
- Actions Speak Louder Than Words: Rate-Reward Trade-off in Markov Decision Processes (ICLR 2025 · similarity 0.90)
- Minimum Entropy Coupling with Bottleneck (NeurIPS 2024 · similarity 0.88)
- Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs (NeurIPS 2024 · similarity 0.85)
- RGMComm: Return Gap Minimization via Discrete Communications in Multi-Agent Reinforcement Learning (AAAI 2024 · similarity 0.85)
- Learning in Markov Games with Adaptive Adversaries: Policy Regret, Fundamental Barriers, and Efficient Algorithms (NeurIPS 2024 · similarity 0.85)
- Learning Equilibria in Adversarial Team Markov Games: A Nonconvex-Hidden-Concave Min-Max Optimization Problem (NeurIPS 2024 · similarity 0.85)
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