StarCraft (Blizzard Entertainment, 1998) is a real-time strategy video game, placing the player in command of three extraterrestrial races fighting against each other for strategic control of ...resources, terrain, and power. Simon Dor examines the game’s unanticipated effect by delving into the history of the game and the two core competencies it encouraged: decoding and foreseeing. Although StarCraft was not designed as an e-sport, its role in developing foreseeing skills helped give rise to one of the earliest e-sport communities in South Korea. Apart from the game’s clear landmark status, StarCraft offers a unique insight into changes in gaming culture and, more broadly, the marketability and profit of previously niche areas of interest. The book places StarCraft in the history of real-time strategy games in the 1990s—Dune II, Command & Conquer, Age of Empires—in terms of visual style, narrative tropes, and control. It shows how design decisions, technological infrastructures, and a strong contribution from its gaming community through Battle.net and its campaign editor were necessary conditions for the flexibility it needed to grow its success. In exploring the fanatic clusters of competitive players who formed the first tournaments and professionalized gaming, StarCraft shows that the game was key to the transition towards foreseeing play and essential to competitive gaming and e-sports.
Nash equilibrium, as an essential strategic profile in game theory, is of both practical relevance and theoretical significance due to its wide penetration into various fields, such as smart grids, ...wireless communication networks, and networked mobile vehicles. In particular, distributed Nash equilibrium seeking strategies have recently attracted increasing attention because they show remarkable advantages in relaxing the requirement of a central node for information broadcasting or full observation of players' actions. This article aims to provide a survey of distributed Nash equilibrium seeking in games with partial decision information, in which players can only exchange information with their neighbors and their objective functions may explicitly depend on all players' actions. First, fundamental problem descriptions on distributed Nash equilibrium seeking are presented. Second, related results on distributed Nash equilibrium seeking in general multiplayer games, aggregative games, and multicluster games are reviewed, respectively, where representative continuous- and discrete-time methods are explained in detail. Third, two practical applications, including collaborative control for a network of mobile sensors and energy consumption control in smart grids, are provided to demonstrate the applicability of distributed Nash equilibrium seeking strategies. Finally, some promising directions are suggested for future research.
In two-player repeated games, zero-determinant (ZD) strategies enable a player to unilaterally enforce a linear payoff relation between her own and her opponent's payoff irrespective of the ...opponent's strategy. This manipulative nature of the ZD strategies attracted significant attention from researchers due to their close connection to controlling distributively the outcome of evolutionary games in large populations. In this article, necessary and sufficient conditions are derived for a payoff relation to be enforceable in multiplayer social dilemmas with a finite expected number of rounds that is determined by a fixed and common discount factor. Thresholds exist for such a discount factor above which desired payoff relations can be enforced. Our results show that depending on the group size and the ZD strategist's initial probability to cooperate their existing extortionate, generous, and equalizer ZD strategies. The threshold discount factors rely on the desired payoff relation and the variation in the single-round payoffs. To show the utility of our results, we apply them to multiplayer social dilemmas, and show how discounting affects ZD Nash equilibria.
This article considers consensus of first-order/second-order hybrid multiagent systems (MASs) based on game modeling. In the first-order hybrid MAS (HMAS), a subset of agents select the Nash ...equilibrium of a multiplayer game as their states at each game time and the others update their states with first-order continuous-time (C-T) dynamics. By graph theory and matrix theory, we establish sufficient and necessary conditions for consensus of the first-order HMAS with two proposed protocols. The second-order HMAS is composed of agents whose states are determined by the Nash equilibrium of a multiplayer game and agents whose states are governed by second-order C-T dynamics. Similarly, sufficient and necessary conditions are given for consensus of the second-order HMAS with two proposed protocols. Several numerical simulations are provided to verify the effectiveness of our theoretical results.
This study introduces the ludic ethics approach for understanding the moral deliberations of players of online multiplayer games. Informed by a constructivist paradigm that places players’ everyday ...ethical negotiations at the forefront of the analysis, this study utilises a novel set of game-related moral vignettes in a series of 20 in-depth interviews with players. Reflexive thematic analysis of these interviews produced four key themes by which participants considered the ethics of in-game actions: (1) game boundaries, (2) consequences for play, (3) player sensibilities, and (4) virtuality. These results support the conceptualisation of games as complex ethical sites in which players negotiate in-game ethics by referring extensively – although not exclusively – to a framework of ‘ludomorality’ that draws from the interpreted meanings associated with the ludic digital context.
•We study the evolutionary dynamics of multiplayer ZD strategies.•Either extortionate ZD strategies or generous ZD strategies stabilize in the space of ZD strategies.•Extortionate ZD strategies must ...extort severely to evolve.•Generous ZD strategies reciprocating opponents but to a limited degree can evolve.•Evolution leads to generosity rather than extortion when few individuals interact repeatedly.
Several studies have confirmed the existence of zero-determinant (ZD) strategies in repeated social dilemmas since Press and Dyson’s ingenious discovery of ZD strategies in iterated prisoner’s dilemmas. However, less research studies evolutionary performance of multiplayer ZD strategies, especially from a theoretical perspective. Here, we use a state-clustering method to theoretically analyze evolutionary dynamics of two representative ZD strategies: generous ZD strategies and extortionate ZD strategies. We consider two new settings for multiplayer ZD strategies: competitions with all ZD strategies and competitions with all memory-one strategies, apart from the competitions between these strategies and some classical ones. Moreover, we investigate the influence of the level of generosity and extortion on evolutionary dynamics of generous and extortionate ZD strategies, which was commonly ignored in previous studies. Theoretical results show that players with limited generosity are at an advantageous place and extortioners extorting more severely hold their ground more readily. Our results may provide new insights into better understanding evolutionary dynamics of ZD strategies in repeated multiplayer games.
Personalization of game difficulty is a critical task in leveraging artificial intelligence (AI) technologies to enhance player engagement in virtual worlds like metaverse. One of the key challenges ...in this area is developing methods for assessing a player’s perception of game difficulty. This information can be used to dynamically adjust the game difficulty to match the player’s skill level and preferences, which can improve the player’s experience and engagement. The existing approaches have limitations such as relying on costly external devices, requiring time-consuming feedback or questionnaires, and being specific to certain game genres and narratives. In this paper, we propose a new method called ChatDDA for evaluating a player’s perception of game difficulty by analyzing the content of their chat messages. Our method uses a pre-trained language model to extract semantic features from the chat messages, which are then used to train a feed-forward neural network to predict the player’s level of hopefulness or despair about succeeding in the game. Three pre-trained language models—BERT, RoBERTa, and Twitter-roBERTa—are fine-tuned on a purpose-built dataset of player chat messages of the popular multiplayer online game PlayerUnknown’s Battlegrounds (PUBG) tagged as expressing optimism or pessimism regarding game success. The results showed that our method can accurately predict a player’s perception of game difficulty, with an accuracy of 0.953 on the test dataset of player chat messages. This suggests that our method has the potential to enhance player engagement and immersion within the game, ultimately leading to more satisfying and enjoyable metaverse experiences.
•Existing approaches rely on external devices or interruptive feedback.•An innovative algorithm to adjust game difficulty based on chat messages.•A well-balanced labeled dataset of 5,200 messages was created.•The proposed method evaluates player optimism/pessimism in the game.•The method predicts player perception of game difficulty with an accuracy of over 95%.
•Some cancerous mutations are cooperative; their invasion can be modelled using public goods games.•We simulate evolutionary dynamics in tissues using the Voronoi tessellation model.•This allows us ...to spatially decouple birth and death and capture a dynamic population structure.•We find cooperation is favoured compared to death-birth processes on fixed graphs.•Cooperation prefers local game play but global competition for offspring.
Cancer cells obtain mutations which rely on the production of diffusible growth factors to confer a fitness benefit. These mutations can be considered cooperative, and studied as public goods games within the framework of evolutionary game theory. The population structure, benefit function and update rule all influence the evolutionary success of cooperators. We model the evolution of cooperation in epithelial cells using the Voronoi tessellation model. Unlike traditional evolutionary graph theory, this allows us to implement global updating, for which birth and death events are spatially decoupled. We compare, for a sigmoid benefit function, the conditions for cooperation to be favoured and/or beneficial for well-mixed and structured populations. We find that when population structure is combined with global updating, cooperation is more successful than if there were local updating or the population were well-mixed. Interestingly, the qualitative behaviour for the well-mixed population and the Voronoi tessellation model is remarkably similar, but the latter case requires significantly lower incentives to ensure cooperation.
Evolutionary dynamics of complex multiple games Venkateswaran, Vandana Revathi; Gokhale, Chaitanya S
Proceedings of the Royal Society. B, Biological sciences,
06/2019, Volume:
286, Issue:
1905
Journal Article
Peer reviewed
Open access
Evolutionary game theory has been successful in describing phenomena from bacterial population dynamics to the evolution of social behaviour. However, it has typically focused on a single game ...describing the interactions between individuals. Organisms are simultaneously involved in many intraspecies and interspecies interactions. Therefore, there is a need to move from single games to multiple games. However, these interactions in nature involve many players. Shifting from 2-player games to multiple multiplayer games yield richer dynamics closer to natural settings. Such a complete picture of multiple game dynamics (MGD), where multiple players are involved, was lacking. For multiple multiplayer games-where each game could have an arbitrary finite number of players and strategies, we provide a replicator equation for MGD having many players and strategies. We show that if the individual games involved have more than two strategies, then the combined dynamics cannot be understood by looking only at individual games. Expected dynamics from single games is no longer valid, and trajectories can possess different limiting behaviour. In the case of finite populations, we formulate and calculate an essential and useful stochastic property, fixation probability. Our results highlight that studying a set of interactions defined by a single game can be misleading if we do not take the broader setting of the interactions into account. Through our results and analysis, we thus discuss and advocate the development of evolutionary game(s) theory, which will help us disentangle the complexity of multiple interactions.
As an important branch of evolutionary game theory, iterated games describe the situations that interacting agents play repeatedly based on previous outcomes by using the conditional strategies. A ...new class of zero-determinant (ZD) strategies, which can control a linear relation between the expected payoffs of a single agent and the coplayers, has dramatically changed the viewpoint on iterated games. Here, in this article, we focus on the decision-making behaviors in iterated multiplayer gaming (IMG) systems with the underlying scenarios of two competing ZDs. The results show that, under the asynchronous best-response dynamics, IMG systems starting from any initial state will converge to Nash equilibrium (NE) in finite time. Particularly, the convergence occurs not only in finite time, but can be limited by the number of strategy switches, which is no more than the total amount of agents in the population. Further studies on calculating the NE points reveal that, there is a threshold for the ZD slope, above which agents with higher baseline payoff dominate, while below which agents of lower baseline payoff prevail. The results of system convergence and NE states highlight the fixation of long-run decision-making behaviors in IMG. Finally, an example of the iterated public goods games is provided for the application of the proposed IMG model.
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