We provide an elementary proof that revenue-maximizing mechanisms exist in multi-parameter settings whenever the distribution of valuations has finite expectation.
The cinematic narratives of modern migrants offer a profound lens through which to explore the complexities of displacement, identity, and belonging in a globalized world. The objective of this paper is to examine how contemporary films, such as Madras Café and Piku, depict the migrant experience, displacement, clashes, cultural hybridity, trauma, and resilience. By analysing a selection of influential films from diverse geographical and cultural contexts, the study highlights the role of cinema in shaping public perceptions of migration while giving voice to marginalized communities. The research employs a multi-modal approach, combining narrative analysis, visual aesthetics, and socio-political critique to unravel the layered representations of migrants in the selected films for the study. Furthermore, it investigates how these narratives challenge stereotypes, foster empathy, and contribute to discourses on trans-nationalism and diaspora. The paper also considers the ethical responsibilities of filmmakers in portraying migrant stories without exploitation. Ultimately, this study underscores cinema's power as both an artistic medium and a tool for social commentary, bridging the gap between personal migrant experiences and broader geopolitical realities.
We provide a geometric proof that the random proposer mechanism is a $4$-approximation to the first-best gains from trade in bilateral exchange. We then refine this geometric analysis to recover the state-of-the-art approximation ratio of $3.15$.
In this paper, we propose a shot percentage distribution strategy among the players of a basketball team to maximize the score that can be achieved by them. The approach is based on the concepts of game theory related to network flow.
In this paper, we construct a winning condition $W$ over a finite set of colors such that, first, every finite arena has a strategy with 2 states of general memory which is optimal w.r.t.~$W$, and second, there exists no $k$ such that every finite arena has a strategy with $k$ states of chromatic memory which is optimal w.r.t.~$W$.
For the problem of prediction with expert advice in the adversarial setting with finite stopping time, we give strong computer evidence that the comb strategy for $k=5$ experts is not asymptotically optimal, thereby giving strong evidence against a conjecture of Gravin, Peres, and Sivan.
Karthik Gajulapalli, James A. Liu, Vijay V. Vazirani
We build on the stability-preserving school choice model introduced and studied recently in [MV18]. We settle several of their open problems and we define and solve a couple of new ones.
We discuss possible criteria that may qualify or disqualify power indices for applications. Instead of providing final answers we merely ask questions that are relevant from our point of view and summarize some material from the literature.
It is well known that the Penrose-Banzhaf index of a weighted game can differ starkly from corresponding weights. Limit results are quite the opposite, i.e., under certain conditions the power distribution approaches the weight distribution. Here we provide parametric examples that give necessary conditions for the existence of limit results for the Penrose-Banzhaf index.
We consider the online problem in which an intermediary trades identical items with a sequence of n buyers and n sellers, each of unit demand. We assume that the values of the traders are selected by an adversary and the sequence is randomly permuted. We give competitive algorithms for two objectives: welfare and gain-from-trade.
We present a three player Bayesian game for which there is no epsilon equilibria in Borel measurable strategies for small enough epsilon, however there are non-measurable equilibria.
We model and study the game mechanisms and human behavior of the anarchy mode in Twitch Plays Pokemon with a pure-jump continuous-time Markov process. We computed the winning probability and expected game time for $1$ player and $N$ players and identified when collaboration helps. A numerical plug-in example is also provided.
We show that the problem of finding an ε-approximate Nash equilibrium in an anonymous game with seven pure strategies is complete in PPAD, when the approximation parameter ε is exponentially small in the number of players.
The game-theoretic version of Kolmogorov's strong law of large numbers says that Skeptic has a strategy forcing the statement of the law in a game of prediction involving Reality, Forecaster, and Skeptic. This note describes a simple matching strategy for Reality.
Exploiting the algebraic structure of the set of bimatrix games, a divide-and-conquer algorithm for finding Nash equilibria is proposed. The algorithm is fixed-parameter tractable with the size of the largest irreducible component of a game as parameter. An implementation of the algorithm is shown to yield a significant performance increase on inputs with small parameters.
An population-centric analysis for a version of the p-beauty contest game is given for the two-player, finite population, and infinite population cases. Winning strategies are characterized in terms of iterative thinking relative to the population. To win the game one needs to iterate more times than the ambient population, but not too many more times depending on the population size and the value of p.
We consider Young (1985)'s characterization of the Shapley value, and give a new proof of this axiomatization. Moreover, as applications of the new proof, we show that Young (1985)'s axiomatization of the Shapley value works on various well-known subclasses of TU games.