(2021) Faster Stackelberg Planning via Symbolic Search and Information Sharing.
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Abstract
Stackelberg planning is a recent framework where a leader and a follower each choose a plan in the same planning task, the leader's objective being to maximize plan cost for the follower. This formulation naturally captures security-related (leader=defender, follower=attacker) as well as robustness- related (leader=adversarial event, follower=agent) scenarios. Solving Stackelberg planning tasks requires solving many related planning tasks at the follower level (in the worst case, one for every possible leader plan). Here we introduce new methods to tackle this source of complexity, through sharing information across follower tasks. Our evaluation shows that these methods can significantly reduce both the time needed to solve follower tasks and the number of follower tasks that need to be solved in the first place.
| Item Type: | Conference or Workshop Item (A Paper) (Paper) |
|---|---|
| Divisions: | Michael Backes (InfSec) |
| Conference: | AAAI National Conference of the American Association for Artificial Intelligence |
| Depositing User: | Patrick Speicher |
| Date Deposited: | 16 Mar 2021 10:43 |
| Last Modified: | 16 Mar 2021 10:43 |
| Primary Research Area: | NRA1: Trustworthy Information Processing |
| URI: | https://publications.cispa.saarland/id/eprint/3383 |
Available Versions of this Item
- Faster Stackelberg Planning via Symbolic Search and Information Sharing. (deposited 16 Mar 2021 10:43) [Currently Displayed]
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