Competitive Resource Allocation Research Articles

Multi-dimensional reasoning in competitive resource allocation games: Evidence from intra-team communication

We experimentally investigate behavior and reasoning in various competitive resource allocation games with large strategy spaces. In the experiment, a team of two players plays as one entity against other teams. Team members communicate with one another before choosing a strategy. We analyze their messages using three different classification approaches and find that the vast majority of players think in terms of dimensions or characteristics of strategies rather than in terms of individual elements of the strategy space. Furthermore, the dimensions’ metric allows linking the reasoning across the different games. Thus, we suggest that multi-dimensional reasoning is a frequently used decision procedure that connects the behavior observed in various resource allocation games.

Competitive Resource Allocation Among Urban Congestion Areas in a Modern Big City

Competitive Resource Allocation Among Urban Congestion Areas in a Modern Big City

Countering terrorist propaganda: Competitive resource allocation to communities

Increased terrorist propaganda has caused greater violence worldwide. Communities are efficient channels through which terrorist organizations can access target audiences; thus, communities are playing larger roles in terrorist propaganda distribution. However, no previous studies have examined the interactions between terrorists and governments regarding terrorist propaganda in communities from a game-theoretic lens. This article aims to fill this research gap. We first classify the relationships between the communities as independent or interactive. For both cases, we describe the process of terrorist propaganda distribution in communities, highlighting the dependence of the degree of terrorist ideology within a community on the terrorist-organization and government resource allocations; based on this, we build novel sequential game models of the terrorist and the government and obtain the equilibrium solutions. Furthermore, we conduct a comparative study to elucidate the differences in the expected government losses for independent and interactive communities. The outcomes are as follows: (i) the higher the community propagation centrality, the greater the resource expenditure of the government and terrorist organization, and (ii) introducing an interaction network among communities decreases the expected government loss when the network directly destroys the distribution uniformity of the community propagation centralities. Finally, we present a case study to illustrate the usability of the proposed models. This study provides novel insights for governments targeting optimal allocation of intervention resources to communities so as to counter terrorist propaganda distributed by a strategic terrorist.

Competitive resource allocation in an attacker-defender game: When citizens become targets of being ingratiated

In the realm of counterterrorism, the role of citizens is crucial. In certain scenarios, such as during epidemics or political conflicts, citizens can become targets of being ingratiated between governments and terrorists. Notably, citizen targets possess distinct characteristics compared to other target types. This article centers on the competitive allocation of resources by the defender and the attacker on citizen targets. First, we incorporate utility functions into contest success functions to capture the subjective preferences of citizen targets. Subsequently, we construct a sequential game model of the defender and the attacker, considering their respective budget constraints. Furthermore, we examine how the investment effectiveness of both players impacts the likelihood of a successful attack, optimal resource allocations, and defense losses. Additionally, we model the relationship between the investment effectiveness and the inherent defense levels of citizen targets. Finally, we present a case study to demonstrate the practical applicability of our proposed model. The article’s findings indicate that (i) achieving the optimal resource allocation should consider a combination of factors, including the effectiveness of defender and attacker investments, the inherent defense levels of citizen targets, and the population sizes of these targets and (ii) acknowledging the positive correlation between inherent defense levels and defense effectiveness, enhancing the inherent defense levels of citizen targets can substantially reduce defense losses. This article provides valuable methods and insights that can benefit government agencies worldwide in efficiently allocating resources to protect vulnerable citizen populations from terrorism risks.

Strategically revealing capabilities in General Lotto games

Can revealing one's competitive capabilities to an opponent offer strategic benefits? In this paper, we address this question in the context of General Lotto games, a class of two-player competitive resource allocation models. We consider an asymmetric information setting where the opponent is uncertain about the resource budget of the other player, and holds a prior belief on its value. We assume the other player, called the signaler, is able to send a noisy signal about its budget to the opponent. With its updated belief, the opponent then must decide to invest in costly resources that it will deploy against the signaler's resource budget in a General Lotto game. We derive the subgame perfect equilibrium to this extensive-form game. In particular, we identify necessary and sufficient conditions for which a signaling policy improves the signaler's resulting performance in comparison to the scenario where it does not send any signal. Moreover, we provide the optimal signaling policy when these conditions are met. Notably we find that for some scenarios, the signaler can effectively double its performance.

No apparent cost of disease resistance on reproductive output in Acropora cervicornis genets used for active coral reef restoration in Florida

As assisted sexual reproduction interventions continue to become embedded within coral reef restoration initiatives, it is important to understand the potential for trade-offs between key traits like reproductive output and disease resistance. Oocyte size and fecundity, quantitative measures of reproductive output and important life-history traits, can be used as proxies for coral reproductive success and health. Sexual reproduction, particularly gametogenesis, is an energetically costly process and at the physiological level, trade-offs are caused by competitive allocation of limited resources to various functions. However, resource allocation trade-offs may also have a genetic basis, and thus, different genets may differ in these aspects. Therefore, the purpose of this study was to assess the reproductive output of A. cervicornis genets with known white-band disease resistance or susceptibility by quantifying the number and size of oocytes within colonies maintained within Mote Marine Laboratory’s offshore coral spawning nursery in the Lower Florida Keys, USA. We also quantified the number of eggs and sperm packaged within gamete bundles that were collected during the August 2020 spawning event. Consistent with previous studies, we found a positive correlation between colony size and fecundity. Interestingly though, we found no evidence for a trade-off between disease resistance and reproductive output and instead found a negative correlation between disease susceptibility and oocyte size. These data are relevant for population management interventions and for managing broodstock used for active restoration where a suite of corals with different genotypes and phenotypes are continuously propagated and outplanted. Having a more comprehensive understanding of the fitness differences among candidates can help guide such efforts and ensure that a diversity of fit genets is used for restoration, which should ultimately support greater adaptive potential and population resilience.

Synthesis of Cost-Optimal Multi-Agent Systems for Resource Allocation

Multi-agent systems for resource allocation (MRAs) have been introduced as a concept for modelling competitive resource allocation problems in distributed computing. An MRA is composed of a set of agents and a set of resources. Each agent has goals in terms of allocating certain resources. For MRAs it is typically of importance that they are designed in a way such that there exists a strategy that guarantees that all agents will achieve their goals. The corresponding model checking problem is to determine whether such a winning strategy exists or not, and the synthesis problem is to actually build the strategy. While winning strategies ensure that all goals will be achieved, following such strategies does not necessarily involve an optimal use of resources. In this paper, we present a technique that allows to synthesise cost-optimal solutions to distributed resource allocation problems. We consider a scenario where system components such as agents and resources involve costs. A multi-agent system shall be designed that is cost-minimal but still capable of accomplishing a given set of goals. Our approach synthesises a winning strategy that minimises the cumulative costs of the components that are required for achieving the goals. The technique is based on a propositional logic encoding and a reduction of the synthesis problem to the maximum satisfiability problem (Max-SAT). Hence, a Max-SAT solver can be used to perform the synthesis. From a truth assignment that maximises the number of satisfied clauses of the encoding a cost-optimal winning strategy as well as a cost-optimal system can be immediately derived.

Machine Learning in NextG Networks via Generative Adversarial Networks

Generative Adversarial Networks (GANs) are Machine Learning (ML) algorithms that have the ability to address competitive resource allocation problems together with detection and mitigation of anomalous behavior. In this paper, we investigate their use in next-generation (NextG) communications within the context of cognitive networks to address <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i)</i> spectrum sharing, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii)</i> detecting anomalies, and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">iii)</i> mitigating security attacks. GANs have the following advantages. First, they can learn and synthesize field data, which can be costly, time consuming, and nonrepeatable. Second, they enable pre-training classifiers by using semi-supervised data. Third, they facilitate increased resolution. Fourth, they enable the recovery of corrupted bits in the spectrum. The paper provides the basics of GANs, a comparative discussion on different kinds of GANs, performance measures for GANs in computer vision and image processing as well as wireless applications, a number of datasets for wireless applications, performance measures for general classifiers, a survey of the literature on GANs for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i)–iii)</i> above, and future research directions. As a use case of GAN for NextG communications, we show that a GAN can be effectively applied for anomaly detection in signal classification (e.g., user authentication) outperforming another state-of-the-art ML technique, an autoencoder.

Distributed Resource Allocation in RF-Powered Cognitive Ambient Backscatter Networks

Ambient backscatter communications has shown the great potentials to achieve spectrum and energy efficient communications for future wireless networks (e.g., 6G). Besides, to fully exploit the ambient RF environment, backscatter communications can be combined with RF-powered cognitive networks which brings more reliable and flexible communications. In such networks, a cognitive user pair could communicate through active transmission or backscattering existing signals. In this work, we investigate the distributed resource allocation in terms of channel selection and backscatter power allocation in such setting. A unified framework integrating stochastic geometry and evolutionary game is proposed to model and analyze the distributed resource allocation. Specifically, stochastic geometry is used to analyze the average performance for users considering different communication modes. Then with the average performance obtained, evolutionary game theory is used to model the competitive resource allocation, and replicator dynamics is used to capture the dynamic change of user selections. Based on the formulated evolutionary game, a distributed channel selection and backscatter power allocation algorithm is proposed. Simulations have been performed which validate the theoretical analysis. Also the effectiveness of the proposed scheme is verified.

Ageing as “early-life inertia”: Disentangling life-history trade-offs along a lifetime of an individual

The theory that ageing evolves because of competitive resource allocation between the soma and the germline has been challenged by studies showing that somatic maintenance can be improved without impairing reproduction. However, it has been suggested that cost‐free improvement in somatic maintenance is possible only under a narrow range of benign conditions. Here, we show that experimental downregulation of insulin/IGF‐1 signaling (IIS) in C. elegans nematodes, a robustly reproducible life span‐ and health span‐extending treatment, reduces fitness in a complex variable environment when initiated during development but does not reduce fitness when initiated in adulthood. Thus, our results show that the costs and benefits of reduced IIS can be uncoupled when organisms inhabit variable environments, and, therefore, do not provide support for the resource allocation theory. Our findings support the theory that the force of natural selection on gene expression in evolutionarily conserved signaling pathways that shape life‐history traits declines after the onset of reproduction resulting in organismal senescence.

The Benefits of Fractionation in Competitive Resource Allocation

The Benefits of Fractionation in Competitive Resource Allocation

Cost-free lifespan extension via optimization of gene expression in adulthood aligns with the developmental theory of ageing.

Ageing evolves because the force of selection on traits declines with age but the proximate causes of ageing are incompletely understood. The ‘disposable soma’ theory of ageing (DST) upholds that competitive resource allocation between reproduction and somatic maintenance underpins the evolution of ageing and lifespan. In contrast, the developmental theory of ageing (DTA) suggests that organismal senescence is caused by suboptimal gene expression in adulthood. While the DST predicts the trade-off between reproduction and lifespan, the DTA predicts that age-specific optimization of gene expression can increase lifespan without reproduction costs. Here we investigated the consequences for lifespan, reproduction, egg size and individual fitness of early-life, adulthood and post-reproductive onset of RNAi knockdown of five ‘longevity’ genes involved in key biological processes in Caenorhabditis elegans. Downregulation of these genes in adulthood and/or during post-reproductive period increases lifespan, while we found limited evidence for a link between impaired reproduction and extended lifespan. Our findings demonstrate that suboptimal gene expression in adulthood often contributes to reduced lifespan directly rather than through competitive resource allocation between reproduction and somatic maintenance. Therefore, age-specific optimization of gene expression in evolutionarily conserved signalling pathways that regulate organismal life histories can increase lifespan without fitness costs.

Data-Driven Planning of Electric Vehicle Charging Infrastructure: A Case Study of Sydney, Australia

With the increase of vehicle travelling range and the decrease of vehicle expense, Electric Vehicles (EVs) are gaining popularity as a new transport option which offers a great opportunity for creating a smart city in terms of transportation electrification. However, the existing research of EV charger planning primarily concentrates on the optimal location seeking from a perspective of global optimization. To achieve a competitive strategy in future, a market-based mechanism is proposed for the problem of EV charger planning with a case study of Sydney where a predict-then-optimise diagram is introduced to predict the EV charging demand by a multi-relation graph convolutional network (GCN)-based encoder-decoder deep architecture and optimise the competitive resource allocation strategy for the charger planning through a Cournot competition game model. A new parallel computational algorithm is proposed to seek the Cournot competition equilibrium with the convergence analysis. Furthermore, the optimal EV charger sizing problem is considered to obtain each service provider’s EV charger number at each zone of the city. Experiments are implemented by using the Sydney public transportation dataset and the corresponding key economic indicators. The results show the effectiveness of our proposed approach which can fill the gap between data and the optimal EV charging infrastructure planning.

Perceived Loudness Sensitivity Influenced by Brightness in Urban Forests: A Comparison When Eyes Were Opened and Closed

Soundscape plays a positive, health-related role in urban forests, and there is a competitive allocation of cognitive resources between soundscapes and lightscapes. This study aimed to explore the relationship between perceived loudness sensitivity and brightness in urban forests through eye opening and closure. Questionnaires and measuring equipment were used to gather soundscape and lightscape information at 44 observation sites in urban forested areas. Diurnal variations, Pearson’s correlations, and formula derivations were then used to analyze the relationship between perception sensitivity and how perceived loudness sensitivity was influenced by lightscape. Our results suggested that soundscape variation plays a role in audio–visual perception in urban forests. Our findings also showed a gap in perception sensitivity between loudness and brightness, which conducted two opposite conditions bounded by 1.24 dBA. Furthermore, we found that the effect of brightness on perceived loudness sensitivity was limited if variations of brightness were sequential and weak. This can facilitate the understanding of individual perception to soundscape and lightscape in urban forests when proposing suitable design plans.

Competitive resource allocation to metabolic pathways contributes to overflow metabolisms and emergent properties in cross-feeding microbial consortia.

Resource scarcity is a common stress in nature and has a major impact on microbial physiology. This review highlights microbial acclimations to resource scarcity, focusing on resource investment strategies for chemoheterotrophs from the molecular level to the pathway level. Competitive resource allocation strategies often lead to a phenotype known as overflow metabolism; the resulting overflow byproducts can stabilize cooperative interactions in microbial communities and can lead to cross-feeding consortia. These consortia can exhibit emergent properties such as enhanced resource usage and biomass productivity. The literature distilled here draws parallels between in silico and laboratory studies and ties them together with ecological theories to better understand microbial stress responses and mutualistic consortia functioning.

Competitive Resource Allocation in HetNets: The Impact of Small-Cell Spectrum Constraints and Investment Costs

Heterogeneous wireless networks with small-cell deployments in licensed and unlicensed spectrum bands are a promising approach for expanding wireless connectivity and service. As a result, wireless service providers (SPs) are adding small-cells to augment their existing macro-cell deployments. This added flexibility complicates network management, in particular, service pricing and spectrum allocations across macro- and small-cells. Further, these decisions depend on the degree of competition among SPs. Restrictions on shared spectrum access imposed by regulators, such as low power constraints that lead to small-cell deployments, along with the investment cost needed to add small cells to an existing network, also impact strategic decisions and market efficiency. If the revenue generated by small-cells does not cover the investment cost, then there will be no deployment even if it increases social welfare. We study the implications of such spectrum constraints and investment costs on resource allocation and pricing decisions by competitive SPs, along with the associated social welfare. Our results show that while the optimal resource allocation taking constraints and investment into account can be uniquely determined, adding those features with strategic SPs can have a substantial effect on the equilibrium market structure.

IMPROVING THE EFFICIENCY OF EXPENDITURE FOR FINANCIAL SUPPORT COMPREHENSIVE SERVICES

The article presents the author developed proposals to improve the financial mechanism of the federal budget spending on fi nancial support services in the field of general education. The approaches to the budgetary allocations for the provision of educational services in accordance with the results of the activities of agencies and their providers in a competitive resource allocation. The aim of the article is to solve scientific and practical task of improving the effi ciency of budget spending on general education. Tasks article. Identify ways of improving the fi nancial mechanism of the Russian Federation budget spending on general education and to develop a set of measures for their implementation. Results. The author suggests an approach to planning and budgetary allocations based on performance monitoring results and the eff ectiveness of budget expenditures: The allocation of grants for other purposes from the Russian Federation budget, in addition to grants for fi nancial support for the implementation of the state (municipal) task for the provision of educational services by educational institutions, demonstrating the positive dynamics of performance; The inclusion of indicators of quality in the calculation of the funding of the state (municipal) task for the provision of educational services.

Competitive allocation of resources on a network: an agent-based model of air companies competing for the best routes

We present a stylized model of the allocation of resources on a network. By considering as a concrete example the network of sectors of the airspace, where each node is a sector characterized by a maximal number of simultaneously present aircraft, we consider the problem of air companies competing for the allocation of the airspace. Each company is characterized by a cost function, weighting differently punctuality and length of the flight. We consider the model in the presence of pure and mixed populations of types of airline companies and we study how the equilibria depends on the characteristics of the network.

On Games With Coupled Constraints

We study the problem of cost minimization in competitive resource allocation problems, motivated by our previous work on power minimization in MIMO interference systems. Our setup leads to a general cost minimization game in which each player wishes to minimize the cost of its resource consumption while achieving a target utility level. In general, the player strategies are coupled through both their cost functions and their utility functions. Equilibrium exists only for a certain set of target utility levels which in general is a proper set of all achievable utility levels. To characterize the set of equilibrium utility levels, we introduce the dual of a cost minimization game called a utility maximization game in which each player wishes to maximize its utility while keeping the cost of its resource consumption below a cost threshold. We associate the set of equilibrium utility levels with the set of equilibrium of the dual game corresponding to all cost thresholds, and show that the dual game always possesses an equilibrium. We also obtain an inner estimate of the set of equilibrium utility levels in the case of decoupled cost functions by a minimax approach. We then relax the hard constraint on achieving a target utility level, and introduce a weighted cost minimization game which always possesses an equilibrium. We recover the original equilibria through the equilibria of the weighted cost minimization game as the penalty on not achieving the target utility levels increases.

Optimal resource allocation to survival and reproduction in parasitic wasps foraging in fragmented habitats.

Expansion and intensification of human land use represents the major cause of habitat fragmentation. Such fragmentation can have dramatic consequences on species richness and trophic interactions within food webs. Although the associated ecological consequences have been studied by several authors, the evolutionary effects on interacting species have received little research attention. Using a genetic algorithm, we quantified how habitat fragmentation and environmental variability affect the optimal reproductive strategies of parasitic wasps foraging for hosts. As observed in real animal species, the model is based on the existence of a negative trade-off between survival and reproduction resulting from competitive allocation of resources to either somatic maintenance or egg production. We also asked to what degree plasticity along this trade-off would be optimal, when plasticity is costly. We found that habitat fragmentation can indeed have strong effects on the reproductive strategies adopted by parasitoids. With increasing habitat fragmentation animals should invest in greater longevity with lower fecundity; yet, especially in unpredictable environments, some level of phenotypic plasticity should be selected for. Other consequences in terms of learning ability of foraging animals were also observed. The evolutionary consequences of these results are discussed.