78 citations · 333 across the 57 of their papers we have counts for
6 papers · 1 filter
Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows
Lauren Conger, Franca Hoffmann, Eric Mazumdar +1
We propose a novel framework for analyzing the dynamics of distribution shift in real-world systems that captures the feedback loop between learning algorithms and the distribution…
Consistent Conjectural Variations Equilibrium: Characterization & Stability for a Class of Continuous Games
Daniel J. Calderone, Benjamin J. Chasnov, Samuel A. Burden +1
Leveraging tools from the study of linear fractional transformations and algebraic Riccati equations, a local characterization of consistent conjectural variations equilibrium is g…
On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games under Noisy Feedback
Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
This paper studies a variant of two-player zero-sum matrix games, where, at each timestep, the row player selects row , the column player selects column , and the row player…
Stackelberg Games for Learning Emergent Behaviors During Competitive Autocurricula
Boling Yang, Liyuan Zheng, Lillian J. Ratliff +2
Autocurricular training is an important sub-area of multi-agent reinforcement learning~(MARL) that allows multiple agents to learn emergent skills in an unsupervised co-evolving sc…
Human adaptation to adaptive machines converges to game-theoretic equilibria
Benjamin J. Chasnov, Lillian J. Ratliff, Samuel A. Burden
Adaptive machines have the potential to assist or interfere with human behavior in a range of contexts, from cognitive decision-making to physical device assistance. Therefore it i…
Instance-dependent Sample Complexity Bounds for Zero-sum Matrix Games
Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
We study the sample complexity of identifying an approximate equilibrium for two-player zero-sum matrix games. That is, in a sequence of repeated game plays, how many r…