Potential Game Research Articles

Antibody-drug conjugates combined with immunotherapy: a potential game changer in the treatment of upper tract urothelial carcinoma

Currently, treatment strategies for upper tract urothelial carcinoma (UTUC) are changing rapidly. However, there are many limitations in the implementation of new surgical methods and systemic treatment options, which cannot reverse the current status quo of UTUC treatment. In recent years, antibody-drug conjugates have shown great potential in the field of cancer treatment, which can activate the immune system and enhance the effect of immunotherapy while accurately killing targeted tumor cells. The results of multiple clinical trials, including the EV-302 study, have confirmed that combination therapy can improve the survival rate of patients with advanced urothelial cancer, and may replace chemotherapy as the first-line treatment for advanced urothelial cancer. However, there are still a series of challenges in the application of combination therapy in UTUC, such as low level of evidence, adverse reactions, and drug resistance. In the future, it is necessary to focus on clinical trials of UTUC combination therapy, further optimize antibody drug conjugates and immunotherapy drugs to adapt to the disease characteristics of UTUC, and further study the molecular biology characteristics of UTUC to meet this series of challenges.

Identification methods for ordinal potential differential games

This paper introduces two new identification methods for linear quadratic (LQ) ordinal potential differential games (OPDGs). Potential games are notable for their benefits, such as the computability and guaranteed existence of Nash Equilibria. While previous research has analyzed ordinal potential static games, their applicability to various engineering applications remains limited. Despite the earlier introduction of OPDGs, a systematic method for identifying a potential game for a given LQ differential game has not yet been developed. To address this gap, we propose two identification methods to provide the quadratic potential cost function for a given LQ differential game. Both methods are based on linear matrix inequalities (LMIs). The first method aims to minimize the condition number of the potential cost function’s parameters, offering a faster and more precise technique compared to earlier solutions. In addition, we present an evaluation of the feasibility of the structural requirements of the system. The second method, with a less rigid formulation, can identify LQ OPDGs in cases where the first method fails. These novel identification methods are verified through simulations, demonstrating their advantages and potential in designing and analyzing cooperative control systems.

Recent Advances in Gene Therapy for Hemophilia: Projecting the Perspectives.

One of the well-known X-linked genetic disorders is hemophilia, which could be hemophilia A as a result of a mutation in the F8 (factor VIII) gene or hemophilia B as a result of a mutation in the F9 (factor IX) gene, leading to insufficient levels of the proteins essential for blood coagulation cascade. In patients with severe hemophilia, factor VIII or factor IX activities in the blood plasma are considerably low, estimated to be less than 1%. This is responsible for spontaneous or post-traumatic bleeding episodes, or both, leading to disease complications and death. Current treatment of hemophilia relies on the prevention of bleeding, which consists of expensive lifelong replacement infusion therapy of blood plasma clotting factors, their recombinant versions, or therapy with recombinant monoclonal antibodies. Recently emerged gene therapy approaches may be a potential game changer that could reshape the therapeutic outcomes of hemophilia A or B using a one-off vector in vivo delivery and aim to achieve long-term endogenous expression of factor VIII or IX. This review examines both traditional approaches to the treatment of hemophilia and modern methods, primarily focusing on gene therapy, to update knowledge in this area. Recent technological advances and gene therapeutics in the pipeline are critically reviewed and summarized. We consider gene therapy to be the most promising method as it may overcome the problems associated with more traditional treatments, such as the need for constant and expensive infusions and the presence of an immune response to the antibody drugs used to treat hemophilia.

Optimizing the cascade of prevention to protect people from tuberculosis: A potential game changer for reducing global tuberculosis incidence.

The provision of tuberculosis preventive treatment is one of the critical interventions to reduce tuberculosis incidence and ultimately eliminate the disease, yet we still miss appropriate tools for an impactful intervention and treatment coverage remains low. We used recent data, epidemiological estimates, and research findings to analyze the challenges of each step of the cascade of tuberculosis prevention that currently delay the strategy implementation. We addressed research gaps and implementation bottlenecks that withhold key actions in tuberculosis case finding, testing for tuberculosis infection, provision of preventive treatment with safer, shorter regimens and supporting people to complete their treatment. Empowering communities to generate demand for preventive therapy and other prevention services in a holistic manner and providing adequate financial support to sustain implementation are essential requirements. The adoption of an effective, universal monitoring and evaluation system is a prerequisite to provide general and granular insight, and to steer progress of the tuberculosis infection strategy at global and local level.

Edge computing collaborative offloading strategy for space‐air‐ground integrated networks

SummaryDue to geographical factors, it is impossible to build large‐scale communication network infrastructure in remote areas, which leads to poor network communication quality in these areas and a series of delay‐sensitive tasks cannot be timely processed and responded. Aiming at the problem of limited coverage in remote areas, the space‐air‐ground integrated networks (SAGIN) combined with mobile edge computing (MEC) can provide low latency and high reliability transmission for offloading delay‐sensitive tasks for users in remote areas. Considering the strong limitation of satellite resources in the space‐ground integrated network and insufficient energy of local user equipment, firstly, a satellite‐UAV cluster‐ground three‐layer edge computing network architecture is proposed in this paper. Under the condition that the delay requirements of various ground tasks are met, the task offloading problem is transformed into a Stackelberg game between ground user equipment and edge servers. In addition, it is proved that the existence of Nash equilibrium in non‐cooperative game between ground user equipment by using potential game. Finally, a Nash equilibrium iterative offloading algorithm based on Stackelberg game (NEIO‐SG) is proposed to find the optimal offloading strategy for tasks to minimize the system offloading cost and the optimal forwarding percentage strategy for offloading tasks to maximize the utility function of the edge server. Simulation results show that compared to other baseline algorithms, NEIO‐SG reduces the total system latency during task offloading by about 13 and the energy consumption of the edge server by about 35.

Exploring uncharted territory: new frontiers in environmental DNA for tropical fisheries management.

Tropical ecosystems host a significant share of global fish diversity contributing substantially to the global fisheries sector. Yet their sustainable management is challenging due to their complexity, diverse life history traits of tropical fishes, and varied fishing techniques involved. Traditional monitoring techniques are often costly, labour-intensive, and/or difficult to apply in inaccessible sites. These limitations call for the adoption of innovative, sensitive, and cost-effective monitoring solutions, especially in a scenario of climate change. Environmental DNA (eDNA) emerges as a potential game changer for biodiversity monitoring and conservation, especially in aquatic ecosystems. However, its utility in tropical settings remains underexplored, primarily due to a series of challenges, including the need for a comprehensive barcode reference library, an understanding of eDNA behaviour in tropical aquatic environments, standardized procedures, and supportive biomonitoring policies. Despite these challenges, the potential of eDNA for sensitive species detection across varied habitats is evident, and its global use is accelerating in biodiversity conservation efforts. This review takes an in-depth look at the current state and prospects of eDNA-based monitoring in tropical fisheries management research. Additionally, a SWOT analysis is used to underscore the opportunities and threats, with the aim of bridging the knowledge gaps and guiding the more extensive and effective use of eDNA-based monitoring in tropical fisheries management. Although the discussion applies worldwide, some specific experiences and insights from Indian tropical fisheries are shared to illustrate the practical application and challenges of employing eDNA in a tropical context.

Incentive-based fault-tolerant cooperative payoff design in weakly acyclic games

This paper proposes an incentive-based cooperative payoff design method to accommodate faults in weakly acyclic games, where the payoff functions of normal players are designed such that all players’ optimal payoffs are recovered into an admissible level. Besides, the stochastically stable Nash equilibrium (SSNE) is regarded as the optimal state to avoid some inefficient Nash equilibria. Firstly, without cooperation among players, the effect of faults on SSNE and the optimal payoff is analyzed deeply. Further, the conditions of fault accommodation are discussed under the proposed cooperative fault tolerance method, based on which an algorithm is designed to calculate the feasible incentive. Secondly, with cooperation among players, the effect of faults is analyzed again in special weakly acyclic games, namely potential games, and the simpler conditions of fault accommodation are provided. Finally, two examples of frequency assignment in distributed systems and power management in sensor networks illustrate the effectiveness of the proposed methods.

Joint optimization of deployment, user association, channel, and resource allocation for fairness‐aware multi‐UAV network

AbstractThis paper studies the problem of joint deployment, user association, channel, and resource allocation in unmanned aerial vehicle‐enabled access network. Since different user equipments performing different tasks and have different data rate requirements, the priority‐based traffic fairness problem is investigated. This problem, however, is a mixed integer nonlinear programming problem with NP‐hard complexity, making it challenging to be solved. To address this issue, a self‐organized and distributed framework “sense‐as‐you‐fly” based on the decomposition process, which divides the original problem into several subproblems, is proposed. Assuming without central controller, we derive the closed‐form resource allocation scheme and propose distributed many‐to‐one matching to optimize user association subproblem. Considering the coupled characteristics, the multi‐unmanned aerial vehicle deployment and channel allocation subproblems are modelled as a local altruistic game. The existence of Nash equilibrium is proved with the aid of exact potential game and efficient best response learning‐based algorithm is proposed. The original problem is finally addressed by solving the sub‐problems alternately and iteratively. Simulation results verify its effectiveness. By jointly optimizing multidimensional variables, the proposed algorithm unlocks network performance gains, especially in resource‐limited regimes.

Economic impacts of power-to-liquid fuels in aviation: A general equilibrium analysis of production and utilization in Germany

The aviation industry faces an urgent need to adopt sustainable aviation fuels for significant decarbonization. Power-to-Liquid (PtL) fuel is considered a potential game changer, but questions remain about the wider economic impacts of introducing PtL fuel in the aviation sector. This paper examines the economic impacts of introducing PtL fuel blending quotas along with a price policy consisting of a kerosene tax and PtL fuel subsidies for the case of Germany. Based on a detailed supply chain analysis, we apply a social accounting matrix and a computable general equilibrium model to take into account both, the production and utilization perspectives of PtL jet fuel. Our results show that the influence of low blending quotas is mainly limited to the aviation sector, with a 10 % blending quota increasing consumer prices by 7.9 % and reducing aviation industry output by 3.1 %. When quota levels increase, however, the effects go beyond the air transport system. On inter-sectoral level, we identify three main patterns: First, industries that substantially contribute to the PtL fuel supply chain, such as metal products and electrical equipment, see increasing levels in both, domestic production, and imports. Second, aviation upstream industries like transport infrastructure and aircraft production see reduced domestic production and imports. Third, aviation downstream industries, such as delivery services and travel agencies, see substitution effects, where imports partly replace domestic output. Macroeconomic indicators are affected negatively by the quota scenarios, but the relative impact is low as the maximum decrease in the gross domestic product (GDP) does not exceed 0.35 %. PtL fuel production subsidies can largely mitigate the decrease in aviation demand but come at the cost of a stronger reduction in the GDP and government income. Moreover, the sensitivity analysis emphasizes that various assumptions and parameters, such as the cost projections of PtL fuel, import options, and elasticities of demand, affect the intensity of economic consequences. Our analysis implies the trade-offs of policymaking between sectoral and macroeconomic interests in the context of sustainable fuels. The main contribution of this study is the investigation of the broader economic effects resulting from the adoption of PtL fuels in aviation. In particular, the production as well as the utilization perspective are considered simultaneously in this study.

Syrian Immigrants in the Malta Bazaar of Istanbul: Changing Rules of the Trade Game and Negotiation between the Capitals

ABSTRACT This article examines the socio-spatial transformations of the Malta Bazaar in Istanbul and the new Syrian shopkeepers as potential game changers. We argue that the transformation of the bazaar cannot be seen solely as a commercial venture, but can also be read as a dynamic playground of understanding and tolerance, as well as emerging social, cultural and economic contrasts and tensions. To test these arguments, we designed a field study with an ethnographic approach. The central theme of our research is to read the role of Syrians in the social reproduction of space through potential changes in the rules of the game in a micro-space. We adopted Pierre Bourdieu's concepts of field and habitus to relate the micro-level experiences of actors in space to broader macro contexts. As a result, we concluded that the change in the rules of the game should be defined as a process of mutual uneasiness. What happens in the field at this stage is an attempt to fit into a single space where negotiation rather than cooperation is more prominent and mutual compromises are inevitably made.

On equivalence of state-based potential games

On equivalence of state-based potential games

A back‐to‐back coordination‐based learning scheme for deceiving reactive jammers in distributed networks

AbstractReactive jammers select jamming strategies according to the users’ responses; thus, conventional anti‐jamming methods such as frequency hopping are inadequate to defeat the jamming attack. In this article, the authors propose a novel uncoupled deception scheme to trap the reactive jammer into attacking a decoy channel in distributed networks. Specifically, the authors design a multi‐functional network utility for every user to mislead the jammer with a minimum energy consumption while achieving the highest network throughput. Based on the network utility, the anti‐jamming problem is formulated as an exact potential game such that the existence of Nash equilibrium can be guaranteed theoretically. The authors further propose a back‐to‐back coordination‐based learning algorithm to reach the optimal channel selection and power adaption in a non‐cooperative way. To alleviate the lack of mutual information exchange, the back‐to‐back coordination mechanism derives all users to deceive the jammer by inferring others’ strategies based on a shared belief. Simulation results show that the proposed algorithm yields higher network throughput and efficiency‐cost ratio compared to the state‐of‐the‐art cooperative schemes.

Sequential multichannel allocation in cache-enabled multicasting small-cell networks

This paper investigates the optimization of multichannel allocation in cache-enabled multicasting small-cell networks (CMSNs). In the traditional fixed channel allocation scheme (FCA), small-cell base stations (SBSs) allocate a fix channel to each local cache popular content. In order to further increasing the utilization of allocated channels, we first propose a sequential multichannel allocation scheme (SMA), in which SBSs allocate a sequential channel set to their cached files dynamically. We formulate the problem of sequential multichannel allocation as two NP-hard non-linear programming problems with two optimization objectives of minimizing the global collision level (GCL) and maximizing the global file-downloading level (GFL), and demonstrate the advantages of the proposed DSCA over FCA. Then, two channel allocation potential games are proposed to achieve GCL and GFL optimization respectively. To achieve Nash equilibria (NEs) of the proposed games, we present a better response based SMA algorithm (BR-SMA) for both two games, and propose an improved better response based SMA algorithm (IBR-SMA) for the game for GCL maximization which have two exploration modes for each decision-maker.

Safe and Human-Like Autonomous Driving: A Predictor–Corrector Potential Game Approach

Safe and Human-Like Autonomous Driving: A Predictor–Corrector Potential Game Approach

A cloud-edge collaborative computing framework using potential games for space-air-ground integrated IoT

As a critical component of space-air-ground integrated IoT, the aerial network provides highly reliable, low-latency and ubiquitous information services to ground users by virtue of their high mobility, easy deployment and low cost. However, the current computation and resource management model of air-ground integrated networks are insufficient to meet the latency demanding of emerging intelligent services such as autonomous systems, extended reality and haptic feedback. To tackle these challenges, we propose a computation offloading and optimization method based on potential game. First, we construct an cloud-edge collaborative computing model. Secondly, we construct Offloading Decision Objective Functions (ODOF) with the objective of minimum task processing latency and energy consumption. ODOF is proved to be a Mixed Inferior Nonlinear Programming (MINLP) problem, which is hard to solve. ODOF is converted to be a full potential game, and the Nash equilibrium solution exists. Then, a computational resource allocation algorithm based on Karush–Kuhn–Tucker (KKT) conditions is proposed to solve resource allocation problem. On this basis, a distributed game-based computational offloading algorithm is proposed to minimize the offloading cost. Extensive simulation results demonstrate that the convergence performance of the proposed algorithm is reduced by 50%, the convergence time is reduced by 13.3% and the average task processing delay is reduced by 10%.

On the Upper Bound of Near Potential Differential Games

This letter presents an extended analysis and a novel upper bound of the subclass of Linear Quadratic Near Potential Differential Games (LQ NPDG). LQ NPDGs are a subclass of potential differential games, for which there is a distance between an LQ exact potential differential game and the LQ NPDG. LQ NPDGs exhibit a unique characteristic: The smaller the distance from an LQ exact potential differential game, the more closer their dynamic trajectories. This letter introduces a novel upper bound for this distance. Moreover, a linear relation between this distance and the resulting trajectory errors is established, opening the possibility for further application of LQ NPDGs.

A game theoretic approach to wireless body area networks interference control

AbstractIn this paper we consider a scenario where there are two wireless body area networks (WBANs) interfere with each other from a game theoretic perspective. In particular, we envision two WBANs playing a potential game to enhance their performance by decreasing interference to each other. Decreasing interference extends the sensors' batteries life time and reduces the number of re‐transmissions. We derive the required conditions for the game to be a potential game and its associated the Nash equilibrium (NE). Specifically, we formulate a game where each WBAN has three strategies. Depending on the payoff of each strategy, the game can be designed to achieve a desired NE. Furthermore, we employ a learning algorithm to achieve that NE. In particular, we employ the Fictitious play (FP) learning algorithm as a distributed algorithm that WBANs can use to approach the NE. The simulation results show that the NE is mainly a function of the power cost parameter and a reliability factor that we set depending on each WBAN setting (patient). However, the power cost factor is more dominant than the reliability factor according to the linear cost function formulation that we use throughout this work.

Best-response dynamics in two-person random games with correlated payoffs

We consider finite two-player normal form games with random payoffs. Player A's payoffs are i.i.d. from a uniform distribution. Given p∈[0,1], for any action profile, player B's payoff coincides with player A's payoff with probability p and is i.i.d. from the same uniform distribution with probability 1−p. This model interpolates the model of i.i.d. random payoff used in most of the literature and the model of random potential games. First we study the number of pure Nash equilibria in the above class of games. Then we show that, for any positive p, asymptotically in the number of available actions, best response dynamics reaches a pure Nash equilibrium with high probability.

Computing Nash Equilibria in Potential Games with Private Uncoupled Constraints

We consider the problem of computing Nash equilibria in potential games where each player's strategy set is subject to private uncoupled constraints. This scenario is frequently encountered in real-world applications like road network congestion games where individual drivers adhere to personal budget and fuel limitations. Despite the plethora of algorithms that efficiently compute Nash equilibria (NE) in potential games, the domain of constrained potential games remains largely unexplored. We introduce an algorithm that leverages the Lagrangian formulation of NE. The algorithm is implemented independently by each player and runs in polynomial time with respect to the approximation error, the sum of the size of the action-spaces, and the game's inherit parameters.

Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property

Policy gradient methods enjoy strong practical performance in numerous tasks in reinforcement learning. Their theoretical understanding in multiagent settings, however, remains limited, especially beyond two-player competitive and potential Markov games. In this paper, we develop a new framework to characterize optimistic policy gradient methods in multi-player Markov games with a single controller. Specifically, under the further assumption that the game exhibits an equilibrium collapse, in that the marginals of coarse correlated equilibria (CCE) induce Nash equilibria (NE), we show convergence to stationary epsilon-NE in O(1/epsilon^2) iterations, where O suppresses polynomial factors in the natural parameters of the game. Such an equilibrium collapse is well-known to manifest itself in two-player zero-sum Markov games, but also occurs even in a class of multi-player Markov games with separable interactions, as established by recent work. As a result, we bypass known complexity barriers for computing stationary NE when either of our assumptions fails. Our approach relies on a natural generalization of the classical Minty property that we introduce, which we anticipate to have further applications beyond Markov games.