Agents
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
In this paper, we introduce a generalization of the standard Stackelberg Games (SGs) framework: Calibrated Stackelberg Games (CSGs) .
Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
In this paper, we introduce a generalization of the standard Stackelberg Games (SGs) framework: Calibrated Stackelberg Games (CSGs) .
INDICT: Code Generation with Internal Dialogues of Critiques for Both Security and Helpfulness Hung Le
INDICT: a new framework that empowers LLMs with Internal Dialogues of Critiques for both safety and helpfulness guidance.
Zero-sum Polymatrix Markov Games: Equilibrium Collapse and Efficient Computation of Nash Equilibria
One such example is two-player zero-sum Markov games, in which efficient ways to compute a Nash equilibrium are known. Inspired by zero-sum polymatrix normal-form games (Cai et al., 2016), we define a class of zero-sum
