Online and Offline Dynamic Influence Maximization Games Over Social Networks

In this work, we consider dynamic influence maximization games over social networks with multiple players (influencers). The goal of each influencer is to maximize their own reward subject to their limited total budget rate constraints. Thus, influencers need to carefully design their investment policies considering individuals' opinion dynamics and other influencers' investment strategies, leading to a dynamic game problem. We first consider the case of a single influencer who wants to maximize its utility subject to a total budget rate constraint. We study both offline and online versions of the problem where the opinion dynamics are either known or not known a priori. In the singe-influencer case, we propose an online no-regret algorithm, meaning that as the number of campaign opportunities grows, the average utilities obtained by the offline and online solutions converge. Then, we consider the game formulation with multiple influencers in offline and online settings. For the offline setting, we show that the dynamic game admits a unique Nash equilibrium policy and provide a method to compute it. For the online setting and with two influencers, we show that if each influencer applies the same no-regret online algorithm proposed for the single-influencer maximization problem, they will converge to the set of $\epsilon$-Nash equilibrium policies where $\epsilon=O(\frac{1}{\sqrt{K}})$ scales in average inversely with the number of campaign times $K$ considering the average utilities of the influencers. Moreover, we extend this result to any finite number of influencers under more strict requirements on the information structure. Finally, we provide numerical analysis to validate our results under various settings.Comment: This work has been submitted to IEEE for possible publicatio

Separable and Low-Rank Continuous Games

In this paper, we study nonzero-sum separable games, which are continuous games whose payoffs take a sum-of-products form. Included in this subclass are all finite games and polynomial games. We investigate the structure of equilibria in separable games. We show that these games admit finitely supported Nash equilibria. Motivated by the bounds on the supports of mixed equilibria in two-player finite games in terms of the ranks of the payoff matrices, we define the notion of the rank of an n-player continuous game and use this to provide bounds on the cardinality of the support of equilibrium strategies. We present a general characterization theorem that states that a continuous game has finite rank if and only if it is separable. Using our rank results, we present an efficient algorithm for computing approximate equilibria of two-player separable games with fixed strategy spaces in time polynomial in the rank of the game

Multi-Layer Cyber-Physical Security and Resilience for Smart Grid

The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision theory as a tool to model the interactions among system components and the interaction between attackers and the system. We discuss game-theoretic applications and challenges in the design of cross-layer robust and resilient controller, secure network routing protocol at the data communication and networking layers, and the challenges of the information security at the management layer of the grid. The chapter will discuss the future directions of using game-theoretic tools in addressing multi-layer security issues in the smart grid.Comment: 16 page

A Gauge-Gravity Relation in the One-loop Effective Action

We identify an unusual new gauge-gravity relation: the one-loop effective action for a massive spinor in 2n dimensional AdS space is expressed in terms of precisely the same function [a certain multiple gamma function] as the one-loop effective action for a massive charged scalar in 4n dimensions in a maximally symmetric background electromagnetic field [one for which the eigenvalues of F_{\mu\nu} are maximally degenerate, corresponding in 4 dimensions to a self-dual field, equivalently to a field of definite helicity], subject to the identification F^2 \Lambda, where \Lambda is the gravitational curvature. Since these effective actions generate the low energy limit of all one-loop multi-leg graviton or gauge amplitudes, this implies a nontrivial gauge-gravity relation at the non-perturbative level and at the amplitude level.Comment: 6 page

Autonomous Robust Skill Generation Using Reinforcement Learning with Plant Variation

This paper discusses an autonomous space robot for a truss structure assembly using some reinforcement learning. It is difficult for a space robot to complete contact tasks within a real environment, for example, a peg-in-hole task, because of error between the real environment and the controller model. In order to solve problems, we propose an autonomous space robot able to obtain proficient and robust skills by overcoming error to complete a task. The proposed approach develops skills by reinforcement learning that considers plant variation, that is, modeling error. Numerical simulations and experiments show the proposed method is useful in real environments

Adversarial Control in a Delay Tolerant Network

Abstract. We consider a multi-criteria control problem that arises in a delay tolerant network with two adversarial controllers: the source and the jammer. The source’s objective is to choose transmission probabilities so as to maximize the probability of successful delivery of some content to the destination within a deadline. These transmissions are subject to interference from a jammer who is a second, adversarial type controller, We solve three variants of this problem: (1) the static one, where the actions of both players, u and w, are constant in time; (2) the dynamic open loop problem in which all policies may be time varying, but inde-pendent of state, the number of already infected mobiles; and (3) the dynamic closed-loop feedback policies where actions may change in time and may be specified as functions of the current value of the state (in which case we look for feedback Nash equilibrium). We obtain some ex-plicit expressions for the solution of the first game, and some structural results as well as explicit expressions for the others. An interesting out-come of the analysis is that the latter two games exhibit switching times for the two players, where they switch from pure to mixed strategies and vice versa. Some numerical examples included in the paper illustrate the nature of the solutions

Finite density QED1+1 near Lefschetz thimbles

One strategy for reducing the sign problem in finite-density field theories is to deform the path integral contour from real to complex fields. If the deformed manifold is the appropriate combination of Lefschetz thimbles - or somewhat close to them - the sign problem is alleviated. Gauge theories require generalizing the definition of thimble decompositions, and therefore it is unclear how to carry out a generalized thimble method. In this paper we discuss some of the conceptual issues involved by applying this method to QED1+1 at finite density, showing that the generalized thimble method yields correct results with less computational effort than standard methods

Monte Carlo Study of Real Time Dynamics on the Lattice

Monte Carlo studies involving real time dynamics are severely restricted by the sign problem that emerges from a highly oscillatory phase of the path integral. In this Letter, we present a new method to compute real time quantities on the lattice using the Schwinger-Keldysh formalism via Monte Carlo simulations. The key idea is to deform the path integration domain to a complex manifold where the phase oscillations are mild and the sign problem is manageable. We use the previously introduced "contraction algorithm" to create a Markov chain on this alternative manifold. We substantiate our approach by analyzing the quantum mechanical anharmonic oscillator. Our results are in agreement with the exact ones obtained by diagonalization of the Hamiltonian. The method we introduce is generic and, in principle, applicable to quantum field theory albeit very slow. We discuss some possible improvements that should speed up the algorithm

Self-consistent crystalline condensate in chiral Gross-Neveu and Bogoliubov-de Gennes systems

We derive a new exact self-consistent crystalline condensate in the 1+1 dimensional chiral Gross-Neveu model. This also yields a new exact crystalline solution for the one dimensional Bogoliubov-de Gennes equations and the Eilenberger equation of semiclassical superconductivity. We show that the functional gap equation can be reduced to a solvable nonlinear equation, and discuss implications for the temperature-chemical potential phase diagram.Comment: 5 pages, 5 figures; v2 minor corrections, version for PR

Multistable perception elicits compensatory alpha activity in older adults

Multistable stimuli lead to the perception of two or more alternative perceptual experiences that spontaneously reverse from one to the other. This property allows researchers to study perceptual processes that endogenously generate and integrate perceptual information. These endogenous processes appear to be slowed down around the age of 55 where participants report significantly lower perceptual reversals. This study aimed to identify neural correlates of this aging effect during multistable perception utilizing a multistable version of the stroboscopic alternative motion paradigm (SAM: endogenous task) and a control condition (exogenous task). Specifically, age-related differences in perceptual destabilization and maintenance processes were examined through alpha responses. Electroencephalography (EEG) of 12 older and 12 young adults were recorded during SAM and control tasks. Alpha band activity (8–14 Hz) was obtained by wavelet-transformation of the EEG signal and analyzed for each experimental condition. Endogenous reversals induced gradual decrease in posterior alpha activity in young adults which is a replication of previous studies’ findings. Alpha desynchronization was shifted to anterior areas and prevalent across the cortex except the occipital area for older adults. Alpha responses did not differ between the groups in the control condition. These findings point to recruitment of compensatory alpha networks for maintenance of endogenously generated percepts. Increased number of networks responsible for maintenance might have extended the neural satiation duration and led to decreased reversal rates in older adults