A new way to quantify inefficiency
The 36th Stony Brook game theory conference features the New Perspectives on Algorithmic Game Theory Workshop. One of the most anticipated talks is Professor Gonczarowski’s “Quantifying Inefficiency,” Here’s my note: Setup A context is a pair $C=\bigl(X,(\succsim_i)_{i=1}^{n}\bigr)$ where $X$ is a nonempty finite set of alternatives, $n\in\mathbb{N}$, and each $\succsim_i$ is a preference over $\Delta(X)$ satisfying the von Neumann–Morgenstern axioms (hence admitting an expected-utility representation $u_i$, unique up to positive affine transformation). ...