Rational design and development of new-generation photocatalysts with high hydrogen evolution activity is recognized as an effective strategy to settle energy crisis. To this regard, hybrid Au quantum dots embedded in rimous cadmium sulfide nanospheres are synthesized by using a simple hydrothermal process followed photoreduction. The rough surface irregular fissures greatly strengthen their adhesion interaction dots, which effectively facilitates the separation, restrains recombination,...

This article develops a continuous-time primal-dual accelerated method with an increasing damping coefficient for class of convex optimization problems affine equality constraints. analyzes critical values parameters in the proposed and prove that rate convergence terms duality gap function is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$O(\frac{1}{t^2})$</tex-math></inline-formula> by choosing suitable...

In this paper, we consider a stochastic Nash game in which each player minimizes parameterized expectation-valued convex objective function. deterministic regimes, proximal best-response (BR) schemes have been shown to be convergent under suitable spectral property associated with the BR map. However, direct application of scheme settings requires obtaining exact solutions optimization problems at iteration. Instead, propose an inexact generalization solution problem is computed...

A large surface area of catalytic sites and low electric resistance are desirable properties for electrocatalysts that lower the overpotential required electrochemical reactions, such as hydrogen evolution reaction (HER), in this study. In presence polyoxometalate (POM) triblock copolymer pluronic (P123) a hybrid soft template, hydrothermal sulfurization nickel foam leads to formation hollow microsphere, assembled from Ni3S2 motif. Sonication preparing POM+P123 hybrids, while adjusting POM...

This paper studies a distributed stochastic optimization problem over random networks with imperfect communications subject to global constraint, which is the intersection of local constraint sets assigned agents. The cost function sum expectation-valued convex functions. By incorporating augmented Lagrangian technique projection method, approximation--based primal-dual algorithm proposed solve problem. Each agent updates its estimate by using noisy observations gradient and information...

This article considers distributed Nash equilibrium (NE) seeking of strongly monotone aggregative games over a multiagent network. Each player can only observe its own strategy while exchange information with neighbors via communication graph. To solve the problem, we propose algorithm multiple rounds communication, where players need constant their at each iteration. We then prove that our converges to (unique) NE linear convergence rate. further study single-round version algorithm, which...

β-Ni(OH)₂ on Ni foam can be synthesized using a hydrothermal method. The addition of Fe³⁺ during synthesis produced Fe-doped α-Ni(OH)₂ at 120 °C and 240 °C. HER OER activity these materials were investigated through both experiment DFT.

This paper considers an $n$-player stochastic Nash equilibrium problem (NEP) in which the $i$th player minimizes a composite objective $f_i( \bullet ,x_{-i}) + r_i( )$, where $f_i$ is expectation-valued smooth function, $x_{-i}$ tuple of rival decisions, and $r_i$ nonsmooth convex function with efficient prox-evaluation. In this context, we make following contributions. (I) Under suitable monotonicity assumptions on \redpseudogradient map, derive optimal rate statements oracle complexity...

Abstract Lately, there has been a lot of interest in game-theoretic approaches to the trajectory planning autonomous vehicles (AVs). But most methods solve game independently for each AV while lacking coordination mechanisms, and hence result redundant computation fail converge same equilibrium, which presents challenges computational efficiency safety. Moreover, studies rely on strong assumption knowing intentions all other AVs. This paper designs novel vehicle approach resolve safety...

In this article, we explore how to optimize task allocation for robot swarms in dynamic environments, emphasizing the necessity of formulating robust, flexible, and scalable strategies cooperation. We introduce a novel framework using decentralized partially observable Markov decision process (Dec-POMDP), specifically designed distributed swarm networks. At core our methodology is local information aggregation multiagent deep deterministic policy gradient (LIA-MADDPG) algorithm, which merges...

This paper considers an N-player stochastic Nash game in which the i th player minimizes a composite objective f <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> (x)+r (x ), where fi is expectation-valued and ri has efficient prox-evaluation. In this context, we make following contributions. (i) Under strong monotonicity assumption on concatenated gradient map, derive (optimal) rate statements oracle complexity bounds for proposed...

In this paper, we study network linear equations subject to digital communications with a finite data rate, where each node is associated one equation from system of equations. Each holds dynamic state and interacts its neighbors through an undirected connected graph, along link the pair nodes share information. Due rate constraint, builds encoder/decoder pair, which it produces transmitted messages zooming-in finite-level uniform quantizer also generates estimates neighbors' states received...

A distributed randomized PageRank algorithm based on stochastic approximation (SA) is proposed to estimate the importance scores of web pages. Compared with existing methods, given here has wider applications in sense that it can deal a larger class randomizations. The strong consistency estimates proved, and robustness value analyzed as well. Numerical examples are verify obtained theoretic results.

This work considers an aggregative game over time-varying graphs, where each player's cost function depends on its own strategy and the aggregate of competitors' strategies. Though is unknown to any given player, player may interact with neighbors construct estimate aggregate. We design a distributed iterative Tikhonov regularization method in which independently choose steplengths parameters while meeting some overall coordination requirements. Under monotonicity assumption concatenated...

In this article, we consider distributed stochastic optimization over randomly switching networks, where agents collaboratively minimize the average of all agents' local expectation-valued convex cost functions. Due to stochasticity in gradient observations, distributedness functions, and randomness communication topologies, algorithms with an exact convergence guarantee under fixed step-sizes have not been achieved yet. This work incorporates variance reduction scheme into tracking...

In “Asynchronous Schemes for Stochastic and Misspecified Potential Games Nonconvex Optimization,” Lei Shanbhag consider a class of convex stochastic Nash games, possibly corrupted by parametric misspecification characterized nonconvex potential function. The authors present an asynchronous inexact proximal best-response (BR) scheme in which, at any step, randomly selected player computes BR step (via approximation) other players keep their strategies invariant. Misspecification is addressed...

Decision making under uncertainty has been studied extensively over the last 70 years, if not earlier. In field of optimization, models for two-stage, stochastic, linear programming, presented by Dantzig <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> and Beale rid="ref2" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> , are often viewed as basis subsequent development stochastic optimization. This...

In this paper, a novel distributed stochastic approximation algorithm (DSAA) is proposed to seek roots of the sum local functions, each which associated with an agent from multiple agents connected over network. At iteration, updates its estimate for root utilizing noisy observations function and information derived neighboring agents. The key difference existing ones consists in expanding truncations (so it called DSAAWET), by boundedness estimates can be guaranteed without imposing...

Distributed linear algebraic equation over networks, where nodes hold a part of problem data and cooperatively solve the via node-to-node communications, is basic distributed computation task receiving an increasing research attention. Communications network have stochastic nature, with both temporal spatial dependence due to link failures, packet dropouts, or node recreation, etc. In this article, we study convergence rate protocols <inline-formula...