A Unified Approach to Information, Knowledge, and Stability

Within the context of strategic interaction, we provide a unified framework for analyzing information, knowledge, and the "stable" pattern of behavior. We first study the related interactive epistemology and, in particular, show an equivalence theorem between a strictly dominated strategy and a never-best reply in terms of epistemic states. We then explore epistemic foundations behind the fascinating idea of stability due to J. von Neumann and O. Morgenstern. The major features of our approach are: (i)unlike the ad hoc semantic model of knowledge, the state space is constructed by Harsanyi’s types that are explicitly formulated by Epstein and Wang (Econometrica 64, 1996, 1343-1373); (ii)players may have general preferences, including subjective expected utility and non-expected utility; and (iii) players may be boundedly rational and have non-partitional information structuresepistemic games; Harsanyi's types; interactive epistemology; stability; non-expected utility; bounded rationality

Iterated Strict Dominance in General Games

We offer a definition of iterated elimination of strictly dominated strategies (IESDS) for games with (in)finite players, (non)compact strategy sets, and (dis)continuous payoff functions. IESDS is always a well-defined order independent procedure that can be used to solve Nash equilibrium in dominance-solvable games. We characterize IESDS by means of a "stability" criterion, and offer a sufficient and necessary epistemic condition for IESDS. We show by an example that IESDS may generate spurious Nash equilibria in the class of Reny's better-reply secure games. We provide sufficient/necessary conditions under which IESDS preserves the set of Nash equilibria. Nous donnons une définition de l’élimination itérative des stratégies qui sont strictement donimées (EISSD) pour les jeux avec un nombre fini (ou infini) de joueurs , des ensembles de stratégies compactes (ou non-compactes), et des fonctions de gains continues (ou non-continues). Le processus EISSD est bien défini et indépendant de l’ordre d’élimination. Nous donnons une caractérisation du processus EISSD en utilisant un critère de stabilité et offrons une condition épistémologique. Nous démontrons que le processus EISSD peut produire des équilibres faux dans la classe des jeux de meilleures réponses sécuritaires de Reny. Nous donnons des conditions nécessaires et suffisantes pour que le processus EISSD conserve l’ensemble des équilibre de Nash.game theory, strict dominance, iterated elimination, Nash equilibrium, Reny's better-reply secure games., théorie des jeux, dominance stricte, élimination itérative, équilibre de Nash, jeux de meilleures réponses sécuritaires de Reny

A Fast Maximum kk-Plex Algorithm Parameterized by the Degeneracy Gap

Given a graph, the $k$-plex is a vertex set in which each vertex is not adjacent to at most $k-1$ other vertices in the set. The maximum $k$-plex problem, which asks for the largest $k$-plex from a given graph, is an important but computationally challenging problem in applications like graph search and community detection. So far, there is a number of empirical algorithms without sufficient theoretical explanations on the efficiency. We try to bridge this gap by defining a novel parameter of the input instance, $g_k(G)$, the gap between the degeneracy bound and the size of maximum $k$-plex in the given graph, and presenting an exact algorithm parameterized by $g_k(G)$. In other words, we design an algorithm with running time polynomial in the size of input graph and exponential in $g_k(G)$ where $k$ is a constant. Usually, $g_k(G)$ is small and bounded by $O(\log{(|V|)})$ in real-world graphs, indicating that the algorithm runs in polynomial time. We also carry out massive experiments and show that the algorithm is competitive with the state-of-the-art solvers. Additionally, for large $k$ values such as $15$ and $20$, our algorithm has superior performance over existing algorithms.Comment: IJCAI'202

Early Weight Status and Human Capital in Adulthood: A 32-Year Follow-Up of the 1970 British Cohort Study

Objectives: To prospectively evaluate the effects of early weight status (childhood and adolescence) and changes in obesity status on human capital in adulthood.Methods: We employed data from the 1970 Birth Cohort Study in the United Kingdom. Data on height and weight during childhood and adolescence, human capital variables in adulthood were collected from 2,444 participants. Human capital includes cognitive ability, non-cognitive skill, educational attainment and health status. Data were analyzed through linear regression and logistic regression models.Results: Our results showed that obesity during adolescence was negatively associated with cognitive ability (β = −0.83, p < 0.01), educational attainment (β = −0.49, p < 0.01), and some health outcomes; and that underweight in childhood also adversely affected educational attainment in females (β = −0.66, p < 0.05). In terms of changes in obesity status, becoming obese in adolescence negatively affected cognitive ability (β = −1.18, p < 0.01), educational attainment (β = −0.62, p < 0.05) and some health outcomes, remaining obese was associated with all adverse health outcomes.Conclusion: Our results suggest that obesity during adolescence negatively affects a range of human capital outcomes in adulthood, and adolescence is a critical period during which early obesity affects adult human capital

A Novel Multi-Task Learning Empowered Codebook Design for Downlink SCMA Networks

Sparse code multiple access (SCMA) is a promising code-domain non-orthogonal multiple access (NOMA) scheme for the enabling of massive machine-type communication. In SCMA, the design of good sparse codebooks and efficient multiuser decoding have attracted tremendous research attention in the past few years. This paper aims to leverage deep learning to jointly design the downlink SCMA encoder and decoder with the aid of autoencoder. We introduce a novel end-to-end learning based SCMA (E2E-SCMA) design framework, under which improved sparse codebooks and low-complexity decoder are obtained. Compared to conventional SCMA schemes, our numerical results show that the proposed E2E-SCMA leads to significant improvements in terms of error rate and computational complexity

The Detection of Subsynchronous Oscillation in HVDC Based on the Stochastic Subspace Identification Method 1

Abstract: Subsynchronous oscillation (SSO) usually caused by series compensation, power system stabilizer (PSS), high voltage direct current transmission (HVDC) and other power electronic equipment, which will affect the safe operation of generator shafting even the system. It is very important to identify the modal parameters of SSO to take effective control strategies as well. Since the identification accuracy of traditional methods are not high enough, the stochastic subspace identification (SSI) method is proposed to improve the identification accuracy of subsynchronous oscillation modal. The stochastic subspace identification method was compared with the other two methods on subsynchronous oscillation IEEE benchmark model and Xiang-Shang HVDC system model, the simulation results show that the stochastic subspace identification method has the advantages of high identification precision, high operation efficiency and strong ability of anti- noise. Copyright © 2014 IFSA Publishing, S. L