Research map / Multi-agent systems and games / Human-AI and goal-conditioned
Faster Stackelberg Planning via Symbolic Search and Information Sharing
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace IDS with SLS using symbolic bidirectional search and upper-bound reuse, pruning, and cost-bounded FF search | Stackelberg planning · NEW (P, 1018 instances) | coverage: 601 -> 786 | Helped |
| Replace IDS with SLS using symbolic bidirectional search and upper-bound reuse, pruning, and cost-bounded FF search | Stackelberg planning · NET (P, 1018 instances) | coverage: 507 -> 695 | Helped |
| Replace IDS with SLS using LM-cut and upper-bound reuse, pruning, and cost-bounded FF search | Stackelberg planning · OLD (P, 1987 instances) | coverage: 681 -> 651 | Hurt |
| Add symbolic leader search that reuses previously found plans across leader states (ablation) | SLS · Stackelberg planning | number of follower subsolver calls | Helped |
| Add upper-bound function reuse for early termination of follower searches (ablation) | SLS · Stackelberg planning | runtime | Helped |
| Add upper-bound pruning using Π+ (ablation) | SLS · Stackelberg planning | coverage | Helped |
| Add cost-bounded search with the FF heuristic (ablation) | SLS · Stackelberg planning | coverage | Helped |
| Model follower goals as soft goals with utilities (net-benefit planning) | Stackelberg planning · NET benchmarks | runtime | Hurt |
Closest papers by meaning
- Stackelberg Planning: Towards Effective Leader-Follower State Space Search (AAAI 2018 · similarity 0.93)
- Safe Search for Stackelberg Equilibria in Extensive-Form Games (AAAI 2021 · similarity 0.88)
- Learning Optimal Strategies to Commit To (AAAI 2019 · similarity 0.88)
- Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning (ICML 2023 · similarity 0.87)
- Regret Minimization in Stackelberg Games with Side Information (NeurIPS 2024 · similarity 0.85)
- Learning in Stackelberg Mean Field Games: A Non-Asymptotic Analysis (NeurIPS 2025 · similarity 0.85)
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