Game-theoretic Aspects Research Articles

Maximum sustainable yield as a reference point in the presence of fishing effort that follows an ideal free distribution

AbstractThe concept of maximum sustainable yield (MSY), and the underlying Schaefer model, remain relevant in fisheries management today in spite of past difficulties. However, this model is often applied without the consideration of the spatial structure or dynamics of fishing activities. We expand the Schaefer model to account for multiple fishing sites and fishing activities (effort) that follow an ideal free distribution (IFD, a form of Nash equilibrium) driven by exploitation. We explore this conceptual model using both analytical and numerical solutions. MSY across the fishery is unaffected by the spatial structure when fishing is allocated independently within sites. However, in other cases IFD effort dynamics depress MSY and modify the values of associated reference points. The game theoretic aspect of fleet dynamics should be considered in the use of MSY as a management reference point or during the application of the Schaefer model to data‐limited fisheries.

Games of GANs: game-theoretical models for generative adversarial networks

Generative Adversarial Networks (GANs) have recently attracted considerable attention in the AI community due to their ability to generate high-quality data of significant statistical resemblance to real data. Fundamentally, GAN is a game between two neural networks trained in an adversarial manner to reach a zero-sum Nash equilibrium profile. Despite the improvement accomplished in GANs in the last few years, several issues remain to be solved. This paper reviews the literature on the game-theoretic aspects of GANs and addresses how game theory models can address specific challenges of generative models and improve the GAN’s performance. We first present some preliminaries, including the basic GAN model and some game theory background. We then present a taxonomy to classify state-of-the-art solutions into three main categories: modified game models, modified architectures, and modified learning methods. The classification is based on modifications made to the basic GAN model by proposed game-theoretic approaches in the literature. We then explore the objectives of each category and discuss recent works in each class. Finally, we discuss the remaining challenges in this field and present future research directions.

Male services during between-group conflict: the 'hired gun' hypothesis revisited.

In many group-living mammals, philopatric females form the stable core of the group and defend food or shelter against other groups of females. Where males are larger, their participation could give their female group the edge. How can females secure the contribution of males that are neither the father of current infants, nor the dominant male expecting to sire the next generation of infants? It has been proposed that females recruit these males as 'hired guns', receiving social support and copulations in exchange for fighting, against the interests of the dominant male. We first develop the logic of this hypothesis in unprecedented detail by considering the potential pay-off consequences for females and males. We then provide empirical evidence for the existence of hired guns in this context in several primate species. The game-theoretical aspects of the phenomenon remain to be studied, as is the distribution across contexts (e.g. predation avoidance) and species of the hired gun phenomenon. This article is part of the theme issue 'Intergroup conflict across taxa'.

Low-cost electric fencing for peaceful coexistence: An analysis of human-wildlife conflict mitigation strategies in smallholder agriculture

With a growing global population, human-wildlife conflicts (HWCs) are intensifying and cost-effective mitigation strategies to conserve biodiversity and support rural livelihoods become increasingly relevant. This article presents evidence on how low-cost electric fencing (EF) technology can contribute to a peaceful coexistence between farmers and wildlife. Applying an economic analysis, the effectiveness of smallholders' predominant HWC mitigation strategies in Bhutan are assessed. In Bhutan, HWCs are severe and investments in EF are expanding with about 10% of agricultural land already fenced. The analysis reveals high effectiveness and profitability of EF compared with labor-intensive crop guarding strategies despite smallholders' high time preference. EF profitability particularly depends on net labor savings from reduced time-use for crop guarding. Results emphasize the need for collective action at the community level, since due to small landholdings individually operated EF schemes are unprofitable in most cases. The findings are robust across ecological conditions and variations in key parameters, such as the discount rate (reflecting smallholders' time preference) and opportunity cost of labor. Particularly in contexts where hunting is banned, investments in EF technology could be a main ingredient of comprehensive policies for wildlife conservation and agricultural development. Further research is needed to investigate the biological implications of large-scale fencing policies, the relevance of spatial spillover effects and game-theoretic aspects of community-based EF schemes.

Consensus Crash Testing: Exploring Ripple’s Decentralization Degree in Adversarial Environments

The inception of Bitcoin as a peer-to-peer payment system, and its underlying blockchain data-structure and protocol, has led to an increased interest in deploying scalable and reliable distributed-ledger systems that build on robust consensus protocols. A critical requirement of such systems is to provide enough fault tolerance in the presence of adversarial attacks or network faults. This is essential to guarantee liveness when the network does not behave as expected and ensure that the underlying nodes agree on a unique order of transactions over a shared state. In comparison with traditional distributed systems, the deployment of a distributed-ledger system should take into account the hidden game theoretical aspects of such protocols, where actors are competing with each other in an environment which is likely to experience various well-motivated malicious and adversarial attacks. Firstly, this paper discusses the fundamental principles of existing consensus protocols in the context of both permissioned and permissionless distributed-ledger systems. The main contribution of this work deals with observations from experimenting with Ripple’s consensus protocol as it is embodied in the XRP Ledger. The main experimental finding suggests that, when a low percentage of malicious nodes is present, the centralization degree of the network can be significantly relaxed ensuring low convergence times. Those findings are of particular importance when engineering a consensus algorithm that would like to balance security with decentralization.

PRISM-games: verification and strategy synthesis for stochastic multi-player games with multiple objectives

PRISM-games is a tool for modelling, verification and strategy synthesis for stochastic multi-player games. These allow models to incorporate both probability, to represent uncertainty, unreliability or randomisation, and game-theoretic aspects, for systems where different entities have opposing objectives. Applications include autonomous transport, security protocols, energy management systems and many more. We provide a detailed overview of the PRISM-games tool, including its modelling and property specification formalisms, and its underlying architecture and implementation. In particular, we discuss some of its key features, which include multi-objective and compositional approaches to verification and strategy synthesis. We also discuss the scalability and efficiency of the tool and give an overview of some of the case studies to which it has been applied.

Teams in Online Scheduling Polls: Game-Theoretic Aspects

Consider an important meeting to be held in a team-based organization. Taking availability constraints into account, an online scheduling poll is being used in order to decide upon the exact time of the meeting. Decisions are to be taken during the meeting, therefore each team would like to maximize its relative attendance (i.e. the proportional number of its team members attending the meeting). We introduce a corresponding game, where each team can declare a lower total availability in the scheduling poll in order to improve its relative attendance—the pay-off. We are especially interested in situations where teams can form coalitions. We provide an efficient algorithm that, given a coalition, finds an optimal way for each team in a coalition to improve its pay-off. In contrast, we show that deciding whether such a coalition exists is NP-hard. We also study the existence of Nash equilibria: Finding Nash equilibria for various small sizes of teams and coalitions can be done in polynomial time while it is coNP-hard if the coalition size is unbounded.

Collective decision making with a mix of majority and minority seekers.

We study a model of a population making a binary decision based on information spreading within the population, which is fully connected or covering a square grid. We assume that a fraction of the population wants to make the choice of the minority, whereas the rest want to make the majority choice. This resembles opinion spreading with "contrarian" agents but has the game theoretic aspect that agents try to optimize their own situation in ways that are incompatible with the common good. When this fraction is less than 1/2, the population can efficiently self-organize to a state where agents get what they want-the majority (i.e., the majority seekers) have one opinion, the minority seekers have the other. If the fraction is larger than 1/2, there is a frustration in the population that dramatically changes the dynamics. In this region, the population converges, through some distinct phases, to a state of approximately equal-sized opinions. Just over the threshold the state of the population is furthest from the collectively optimal solution.

Special Issue on Logical Aspects of Multi-Agent Systems

There is a growing interdisciplinary community of researchers and research groups working on logical aspects of MAS from the perspectives of logic, artificial intelligence, computer science, game theory, etc. The workshop Logical Aspects of Multi-Agent Systems (LAMAS) serves the community as a platform for presentation, exchange, and publication of ideas. The idea for and the name of LAMAS actually emerged independently at two locations: in 2002 and 2007, Hans van Ditmarsch organised two editions of LAMAS in Dunedin, New Zealand. From 2010, the community around the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS) saw the need for a workshop on logical aspects of multi-agent systems, and the workshop LAMAS has since been held in Toronto, Canada (2010), Osuna, Spain (2011), Valencia, Spain (2012), Toulouse, France (2013), and Paris, France (2014), with the editions in even years being colocated with AAMAS. In this special issues we present the post-proceedings of the 7th LAMAS, together with extended versions of selected papers of the 15th AAMAS, which were both held in Paris (2014). We invited authors of selected papers to submit extended versions of their papers to this special issue. All submissions had to pass a fresh selection process according to the standards of Studia Logica. We believe that the two selection processes resulted in a collection of papers of high quality. The contributions address different facets of logical aspects of multi-agent systems, including the decidability of multi-agent logics, model checking, logics for agent/robot reasoning and game-theoretical aspects.

Kernel Recursive Least Squares Function Approximation in Game Theory Based Control

A game theoretic aspect in reinforcement learning based controller design with kernel recursive least squares algorithm for value function approximation is proposed in this paper. A kernel recursive least-squares-support vector machine is used to realize a mapping from state, controller's action and disturber's action to Q-value function. Online sparsification framework permits the addition of training sample into the Q-function approximation only if it is approximately linearly independent of the preceding training samples. Markov game setup is shown to be one of the important platforms for addressing robustness of direct adaptive optimal control of nonlinear systems. A game against nature strategy shows the strength of state importance in terms of accelerated learning, and better relative stability of the system. Simulation results on two-link robot manipulator show that the proposed method has high learning efficiency—better accuracy measured in terms of mean square error; and lesser computation time, compared to the least-squares support vector machine.

A Model of Evolutionary Dynamics with Quasiperiodic Forcing

Evolutionary dynamics combines game theory and nonlinear dynamics to model competition in biological and social situations. The replicator equation is a standard paradigm in evolutionary dynamics. The growth rate of each strategy is its excess fitness: the deviation of its fitness from the average. The game-theoretic aspect of the model lies in the choice of fitness function, which is determined by a payoff matrix.Previous work by Ruelas and Rand investigated the Rock-Paper-Scissors replicator dynamics problem with periodic forcing of the payoff coefficients. This work extends the previous to consider the case of quasiperiodic forcing. This model may find applications in biological or social systems where competition is affected by cyclical processes on different scales, such as days/years or weeks/years.We study the quasiperiodically forced Rock-Paper-Scissors problem using numerical simulation, and Floquet theory and har- monic balance. We investigate the linear stability of the interior equilibrium point; we find that the region of stability in frequency space has fractal boundary.

Dominant Strategies of Quantum Games on Quantum Periodic Automata

Game theory and its quantum extension apply in numerous fields that affect people’s social, political, and economical life. Physical limits imposed by the current technology used in computing architectures (e.g., circuit size) give rise to the need for novel mechanisms, such as quantum inspired computation. Elements from quantum computation and mechanics combined with game-theoretic aspects of computing could open new pathways towards the future technological era. This paper associates dominant strategies of repeated quantum games with quantum automata that recognize infinite periodic inputs. As a reference, we used the PQ-PENNY quantum game where the quantum strategy outplays the choice of pure or mixed strategy with probability 1 and therefore the associated quantum automaton accepts with probability 1. We also propose a novel game played on the evolution of an automaton, where players’ actions and strategies are also associated with periodic quantum automata.

Game Theoretic Aspects of the Multi-Channel ALOHA Protocol in Cognitive Radio Networks

In this paper we consider the problem of distributed throughput maximization of cognitive radio networks with the multi-channel ALOHA medium access protocol. First, we characterize the Nash Equilibrium Points (NEPs) of the network when users solve an unconstrained rate maximization (i.e., the total transmission probability equals one). Then, we focus on constrained rate maximization, where user rates are subject to a total transmission probability constraint. We propose a simple best-response algorithm that solves the constrained rate maximization, where each user updates its strategy using its local channel state information (CSI) and by monitoring the channel utilization. We prove the convergence of the proposed algorithm using the theory of potential games. Furthermore, we show that the network approaches a unique equilibrium as the number of users increases. Then, we formulate the problem of choosing the access probability as a leader-followers Stackelberg game, where a single user is chosen to be the leader to manage the network. We show that a fully distributed setup can be applied to approximately optimize the network throughput for a large number of users. Finally, we extend the model to the case where primary and secondary users co-exist in the same frequency band.

POWER INDICES AND THE MEASUREMENT OF CONTROL IN CORPORATE STRUCTURES

This paper proposes a brief review of the use of power indices in the corporate governance literature. Without losing sight of the field of application, it places the emphasis on the game-theoretic aspects of this research and on the issues that arise in this framework. It should be noted that the views presented in this paper are not necessarily those of the IMF.

A review of SIROCCO 2012

Who would have thought that Sirocco winds could one day blow over Iceland? The distributed computing community made it happen by holding the 19th International Colloquium on Structural Information and Communication Complexity (sirocco) in Reykjavik1. With its 120,000 inhabitants, its harbor, small town houses, but crowded bars and many cultural venues, Reykjavik has an air of a village and one of a European metropolis at the same time. In July, the days last forever and so does the hustle and bustle in Reykjavik streets. Reykjavik University, where the conference took place, is located in the southern part of the city, in a newly built campus on the shore, just next to a naturally heated sand beach, and is equipped with modern and pleasant facilities. The fifty or so participants had there the perfect environment to discuss advances in sirocco’s areas of interest. sirocco is devoted to the study of communication and knowledge in distributed systems from both qualitative and quantitative viewpoints. It has been indeed the aim of sirocco, since its 1994 first edition, to comprehend trade-offs and interplay between information that entities are provided in a distributed system and their computational and communication power. Aside from rather traditional problems such as agreement, local decision or graph exploration, new and innovative ones were also given special attention such as problems involving game theoretic aspects and quantum computations. And it is in reflection of this innovative spirit that each year, a Prize for Innovation in Distributed Computing is awarded to individuals whose contribution introduced new approaches or research areas. This year, 28 talks were selected among 54 submitted papers, with Roger Wattenhofer and Boaz Patt-Shamir as invited speakers.

Alternate Models of Replicator Dynamics

Models of evolutionary dynamics are often approached via the replicator equation, which in its standard form is given by ˙ xi = xi ( fi (x)−φ ) , i = 1, . . . ,n, where xi is the frequency of strategy i, fi is its fitness, and φ = Σn i=1 xi fi is the average fitness. A game-theoretic aspect is introduced to the model via the payoff matrix A by taking fi(x) = (A · x)i. This model is based on the exponential model of population growth, ˙ xi = xi fi, with φ introduced in order both to hold the total population constant and to model competition between strategies. We analyze the dynamics of analogous models for the replicator equation of the form ˙ xi = g(xi)( fi −φ ), for selected growth functions g.

Sponsored search auctions: an overview of research with emphasis on game theoretic aspects

We provide a broad overview of the research that has been conducted until recently on the design of sponsored search auctions. We mainly focus on game theoretic and mechanism design aspects of these auctions, and we analyze the issues associated with each of the three participating entities, i.e., the search engine, the advertisers, and the users of the search engine, as well as their resulting behavior. Regarding the search engine, we overview the various mechanisms that have been proposed including the currently used GSP mechanism. The issues that are addressed include analysis of Nash equilibria and their performance, design of alternative mechanisms and aspects of competition among search engines. We then move on to the advertisers and discuss the problem of choosing a bidding strategy, given the mechanism of the search engine. Following this, we consider the end users and we examine how user behavior may create externalities and influence the performance of the advertisers. Finally, we also overview statistical methods for estimating modeling parameters that are of interest to the three entities. In each section, we point out interesting open problems and directions for future research.

Supporting Negotiation Behavior with Haptics-Enabled Human-Computer Interfaces.

An active research goal for human-computer interaction is to allow humans to communicate with computers in an intuitive and natural fashion, especially in real-life interaction scenarios. One approach that has been advocated to achieve this has been to build computer systems with human-like qualities and capabilities. In this paper, we present insight on how human-computer interaction can be enriched by employing the computers with behavioral patterns that naturally appear in human-human negotiation scenarios. For this purpose, we introduce a two-party negotiation game specifically built for studying the effectiveness of haptic and audio-visual cues in conveying negotiation related behaviors. The game is centered around a real-time continuous two-party negotiation scenario based on the existing game-theory and negotiation literature. During the game, humans are confronted with a computer opponent, which can display different behaviors, such as concession, competition, and negotiation. Through a user study, we show that the behaviors that are associated with human negotiation can be incorporated into human-computer interaction, and the addition of haptic cues provides a statistically significant increase in the human-recognition accuracy of machine-displayed behaviors. In addition to aspects of conveying these negotiation-related behaviors, we also focus on and report game-theoretical aspects of the overall interaction experience. In particular, we show that, as reported in the game-theory literature, certain negotiation strategies such as tit-for-tat may generate maximum combined utility for the negotiating parties, providing an excellent balance between the energy spent by the user and the combined utility of the negotiating parties.

Online algorithms with stochastic input

The design and analysis of online algorithms, where the input to the algorithm is revealed over time and the algorithm has to make decisions immediately without knowing the future input, has received a revived interest in the last few years primarily due to their application to online advertising. The canonical problem is the Adwords problem, which is motivated by the problem of optimally allocating ad slots on search queries to budget constrained advertisers. It involves simplifications that ignore certain aspects of the actual way this allocation is done. For instance, it assumes a "first-price" pay-per-impression scheme, ignoring the game theoretic aspects, and considers only one slot per query. To be precise, the Adwords problem is as follows.

Stochastic Switching Games and Duopolistic Competition in Emissions Markets

We study optimal behavior of energy producers under a CO$_2$ emission abatement program. We focus on a two-player discrete-time model where each producer is sequentially optimizing her emission and production schedules. The game-theoretic aspect is captured through a reduced-form price-impact model for the CO$_2$ allowance price. Such duopolistic competition results in a new type of non–zero-sum stochastic switching game with finite horizon. Existence of game Nash equilibria is established through generalization to randomized switching strategies. No uniqueness is possible, and we therefore consider a variety of correlated equilibrium mechanisms. We prove existence of correlated equilibrium points in switching games and give a recursive description of equilibrium game values. A simulation-based algorithm to solve for the game values is constructed, and a numerical example is presented.