Research map / Multi-agent systems and games / Games and equilibria
Non-Cooperative Inverse Reinforcement Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Interleave intent learning with execution instead of learning from prior equilibrium behavior | Defender in N-CIRL versus MA-IRL · Two-stage patrolling game | attacker reward: 4/3 -> 5/6 | Helped |
| Interleave intent learning with execution rather than use MA-IRL strategies | N-CIRL defender · Random cyber-security attack graphs | attacker average reward | Helped |
Closest papers by meaning
- On Feasible Rewards in Multi-Agent Inverse Reinforcement Learning (NeurIPS 2025 · similarity 0.90)
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