šŸ”¬

No?regret Learning in Dynamic Stackelberg Games.

šŸ“… 2022
technical research breakthrough
šŸ”µ Rare

šŸ“– Description

No-Regret Learning in Dynamic Stackelberg Games Niklas Lauffer, Mahsa Ghasemi, Abolfazl Hashemi, Y agiz Savas, and Ufuk Topcu Abstract ? In a Stackelberg game , aleader commits to a randomized strategy, and a follower chooses their best strategy in response. We consider an extension of a stan- dard Stackelberg game, called a discrete-time dynamic Stackelberg game , that has an underlying state space that affects the leader?s rewards and available strategies and evolves in a Markovian manner depending on both the leader and follower?s selected strategies. Although stan- dard Stackelberg games have been utilized to improve scheduling in security domains, their deployment is often limited by requiring complete information of the follower?s utility function. In contrast, we consider scenarios where the follower?s utility function is unknown to the leader; how- ever, it can be linearly parameterized. Our objective then is to provide an algorithm that prescribes a randomized strategy to t...

šŸ“Š Game Impacts

Not verified in game

Which variables this event was proposed to move, and in which direction. The magnitudes are held in the corpus but are not shown here, because they have not been verified against the shipped game. They come from pdoom-data. They describe what an event was proposed to do, not what the shipped game does with it. Most events in the corpus are flavour: they are shown for colour and do not move any game variable. Only a small minority reach the systems below, and several of the variables listed here are not read by the game at all yet. Treat this table as a design proposal under review, not as a measurement of play. Corrections and arguments are welcome — the suggestion links at the foot of this page go straight to the data repo.

Variable Direction Condition
Research proposed: up Always
Papers proposed: up Always
Vibey Doom proposed: up Always

šŸ’­ Reactions

šŸ”¬ Safety Researcher Reaction: āš ļø Placeholder - Needs Real Quote
"Advances our understanding of AI safety"
šŸ“° Media Reaction: āš ļø Placeholder - Needs Real Quote
"Academic research release"
šŸ’” Found a Real Quote? Suggest it here

šŸ”— Sources

šŸ·ļø Event Metadata

Think this event's metadata could be improved? Category and tags describe the real-world event and are maintained in pdoom-data. Rarity, game impacts and p(doom) effects are game-mechanical values owned by pdoom1. Each link below goes to the repository that decides that field.

šŸ“ Category Technical Research Breakthrough ā†’ Suggest different category
ā­ Rarity šŸ”µ Rare ā†’ Suggest different rarity
šŸ·ļø Tags (0) ā†’ Suggest tag changes
šŸ“Š Game Impacts (3) 3 variable changes ā†’ Suggest impact changes
ā˜¢ļø p(Doom) Impact No direct impact ā†’ Suggest p(doom) change
šŸ“ General Metadata Year, description, reactions ā†’ Comprehensive review

šŸ¤ Found an Issue?

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