2 citations · 2 across the 19 of their papers we have counts for
10 papers · 1 filter
Delegating Authorization to Misaligned Agents: Coalitional Alignment and Safe Control
Natalie Collina, Surbhi Goel, Aaron Roth +1
Long-running AI agents create a control problem: each action they take changes the state, which in turn affects the trajectory of future actions. If the agent is not fully aligned,…
Personalization Aids Pluralistic Alignment Under Competition
Natalie Collina, Surbhi Goel, Aaron Roth +1
Can competition among misaligned AI providers yield aligned outcomes for a diverse population of users, and what role does model personalization play? We study a setting where mult…
Swap Regret and Correlated Equilibria Beyond Normal-Form Games
Eshwar Ram Arunachaleswaran, Natalie Collina, Yishay Mansour +3
Swap regret is a notion that has proven itself to be central to the study of general-sum normal-form games, with swap-regret minimization leading to convergence to the set of corre…
Learning to Play Against Unknown Opponents
Eshwar Ram Arunachaleswaran, Natalie Collina, Jon Schneider
We consider the problem of a learning agent who has to repeatedly play a general sum game against a strategic opponent who acts to maximize their own payoff by optimally responding…
The Value of Ambiguous Commitments in Multi-Follower Games
Natalie Collina, Rabanus Derr, Aaron Roth
We study games in which a leader makes a single commitment, and then multiple followers (each with a different utility function) respond. In particular, we study ambiguous commitme…
Algorithmic Collusion Without Threats
Eshwar Ram Arunachaleswaran, Natalie Collina, Sampath Kannan +2
There has been substantial recent concern that pricing algorithms might learn to ``collude.'' Supra-competitive prices can emerge as a Nash equilibrium of repeated pricing games, i…