799 resultados para Game rule encoding
Resumo:
So far in this book, we have seen a large number of methods for generating content for existing games. So, if you have a game already, you could now generate many things for it: maps, levels, terrain, vegetation, weapons, dungeons, racing tracks. But what if you don’t already have a game, and want to generate the game itself? What would you generate, and how? At the heart of any game are its rules. This chapter will discuss representations for game rules of different kinds, along with methods to generate them, and evaluation functions and constraints that help us judge complete games rather than just isolated content artefacts. Our main focus here will be on methods for generating interesting, fun, and/or balanced game rules. However, an important perspective that will permeate the chapter is that game rule encodings and evaluation functions can encode game design expertise and style, and thus help us understand game design. By formalising aspects of the game rules, we define a space of possible rules more precisely than could be done through writing about rules in qualitative terms; and by choosing which aspects of the rules to formalise, we define what aspects of the game are interesting to explore and introduce variation in. In this way, each game generator can be thought of an executable micro-theory of game design, though often a simplified, and sometimes even a caricatured one
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This paper presents a retrospective view of a game design practice that recently switched from the development of complex learning games to the development of simple authoring tools for students to design their own learning games for each other. We introduce how our ‘10% Rule’, a premise that only 10% of what is learnt during a game design process is ultimately appreciated by the player, became a major contributor to the evolving practice. We use this rule primarily as an analytical and illustrative tool to discuss the learning involved in designing and playing learning games rather than as a scientifically and empirically proven rule. The 10% rule was promoted by our experience as designers and allows us to explore the often overlooked and valuable learning processes involved in designing learning games and mobile games in particular. This discussion highlights that in designing mobile learning games, students are not only reflecting on their own learning processes through setting up structures for others to enquire and investigate, they are also engaging in high-levels of independent inquiry and critical analysis in authentic learning settings. We conclude the paper with a discussion of the importance of these types of learning processes and skills of enquiry in 21st Century learning.
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In 2003 Robert Fardon was the first prisoner to be detained under the Dangerous Prisoners (Sexual Offenders) Act 2003 (Qld), the first of the new generation preventive detention laws enacted in Australia and directed at keeping sex offenders in prison or under supervision beyond the expiry of their sentences where a court decides, on the basis of psychiatric assessments, that unconditional release would create an unacceptable risk to the community. A careful examination of Fardon’s case shows the extent to which the administration of the regime was from the outset governed by politics and political calculation rather than the logic of risk management and community protection. In 2003 Robert Fardon was the first person detained under the Dangerous Prisoners (Sexual Offenders) Act 2003 (Qld) (hereafter DPSOA), a newly enacted Queensland law aimed at the preventive detention of sex offenders. It was the first of a new generation of such laws introduced in Australia, now also in force in NSW, Western Australia and Victoria. The laws have been widely criticized by lawyers, academics and others (Keyzer and McSherry 2009; Edgely 2007). In this article I want to focus on the details of how the Queensland law was administered in Fardon’s case, he being perhaps the most well-known prisoner detained under such laws and certainly the longest held. It will show, I hope, that seemingly abstract rule of law principles invoked by other critics are not simply abstract: they afford a crucial practical safeguard against the corruption of criminal justice in which the ends both of community protection and of justice give way to opportunistic exploitation of ‘the mythic resonance of crime and punishment for electoral purposes’ (Scheingold 1998: 888).
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In this chapter, we explore methods for automatically generating game content—and games themselves—adapted to individual players in order to improve their playing experience or achieve a desired effect. This goes beyond notions of mere replayability and involves modeling player needs to maximize their enjoyment, involvement, and interest in the game being played. We identify three main aspects of this process: generation of new content and rule sets, measurement of this content and the player, and adaptation of the game to change player experience. This process forms a feedback loop of constant refinement, as games are continually improved while being played. Framed within this methodology, we present an overview of our recent and ongoing research in this area. This is illustrated by a number of case studies that demonstrate these ideas in action over a variety of game types, including 3D action games, arcade games, platformers, board games, puzzles, and open-world games. We draw together some of the lessons learned from these projects to comment on the difficulties, the benefits, and the potential for personalized gaming via adaptive game design.
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Artificial intelligence (AI) applications typically involve encoding expert knowledge in machine form to find optimal solutions for a given problem. However, this paper deals with the opposite process of extracting new and human-comprehensible insights from emergent AI behaviour. Some examples of useful game-related insights drawn from observing AI players in action are presented.
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We analytically study the role played by the network topology in sustaining cooperation in a society of myopic agents in an evolutionary setting. In our model, each agent plays the Prisoner's Dilemma (PD) game with its neighbors, as specified by a network. Cooperation is the incumbent strategy, whereas defectors are the mutants. Starting with a population of cooperators, some agents are switched to defection. The agents then play the PD game with their neighbors and compute their fitness. After this, an evolutionary rule, or imitation dynamic is used to update the agent strategy. A defector switches back to cooperation if it has a cooperator neighbor with higher fitness. The network is said to sustain cooperation if almost all defectors switch to cooperation. Earlier work on the sustenance of cooperation has largely consisted of simulation studies, and we seek to complement this body of work by providing analytical insight for the same. We find that in order to sustain cooperation, a network should satisfy some properties such as small average diameter, densification, and irregularity. Real-world networks have been empirically shown to exhibit these properties, and are thus candidates for the sustenance of cooperation. We also analyze some specific graphs to determine whether or not they sustain cooperation. In particular, we find that scale-free graphs belonging to a certain family sustain cooperation, whereas Erdos-Renyi random graphs do not. To the best of our knowledge, ours is the first analytical attempt to determine which networks sustain cooperation in a population of myopic agents in an evolutionary setting.
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Looking for a target in a visual scene becomes more difficult as the number of stimuli increases. In a signal detection theory view, this is due to the cumulative effect of noise in the encoding of the distractors, and potentially on top of that, to an increase of the noise (i.e., a decrease of precision) per stimulus with set size, reflecting divided attention. It has long been argued that human visual search behavior can be accounted for by the first factor alone. While such an account seems to be adequate for search tasks in which all distractors have the same, known feature value (i.e., are maximally predictable), we recently found a clear effect of set size on encoding precision when distractors are drawn from a uniform distribution (i.e., when they are maximally unpredictable). Here we interpolate between these two extreme cases to examine which of both conclusions holds more generally as distractor statistics are varied. In one experiment, we vary the level of distractor heterogeneity; in another we dissociate distractor homogeneity from predictability. In all conditions in both experiments, we found a strong decrease of precision with increasing set size, suggesting that precision being independent of set size is the exception rather than the rule.
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This paper showcases the weaknesses of EU enlargement law and demonstrates how one Member State – namely, Greece – is notable for abusing this weakness, for harming the candidate countries, the EU, and the institutions alike, for stripping the EU position of its predictability, and for undermining the EU Commission’s efforts. Accordingly, Greece has severely incapacitated the key procedural rule of law component of the EU’s enlargement regulation, turning it into a randomised political game and ignoring any long-term goals of stability, prosperity, and peace that the process is to stand for. Following a walk through Greece’s engagement throughout a number of enlargement rounds, the paper concludes that the duty of loyalty – which is presumably able to discipline Member States that undermine the common effort – should find a new meaning in the context of EU enlargement.
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Com o aumento de plataformas móveis disponíveis no mercado e com o constante incremento na sua capacidade computacional, a possibilidade de executar aplicações e em especial jogos com elevados requisitos de desempenho aumentou consideravelmente. O mercado dos videojogos tem assim um cada vez maior número de potenciais clientes. Em especial, o mercado de jogos massive multiplayer online (MMO) tem-se tornado muito atractivo para as empresas de desenvolvimento de jogos. Estes jogos suportam uma elevada quantidade de jogadores em simultâneo que podem estar a executar o jogo em diferentes plataformas e distribuídos por um "mundo" de jogo extenso. Para incentivar a exploração desse "mundo", distribuem-se de forma inteligente pontos de interesse que podem ser explorados pelo jogador. Esta abordagem leva a um esforço substancial no planeamento e construção desses mundos, gastando tempo e recursos durante a fase de desenvolvimento. Isto representa um problema para as empresas de desenvolvimento de jogos, e em alguns casos, e impraticável suportar tais custos para equipas indie. Nesta tese e apresentada uma abordagem para a criação de mundos para jogos MMO. Estudam-se vários jogos MMO que são casos de sucesso de modo a identificar propriedades comuns nos seus mundos. O objectivo e criar uma framework flexível capaz de gerar mundos com estruturas que respeitam conjuntos de regras definidas por game designers. Para que seja possível usar a abordagem aqui apresentada em v arias aplicações diferentes, foram desenvolvidos dois módulos principais. O primeiro, chamado rule-based-map-generator, contem a lógica e operações necessárias para a criação de mundos. O segundo, chamado blocker, e um wrapper à volta do módulo rule-based-map-generator que gere as comunicações entre servidor e clientes. De uma forma resumida, o objectivo geral e disponibilizar uma framework para facilitar a geração de mundos para jogos MMO, o que normalmente e um processo bastante demorado e aumenta significativamente o custo de produção, através de uma abordagem semi-automática combinando os benefícios de procedural content generation (PCG) com conteúdo gráfico gerado manualmente.
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When a stable matching rule is used for a college admission market, questions on incentives facing agents of both sides of the market naturally emerge. This note states and proves four important results which fill a gap in the theory of incentives for the college admission model. Two of them have never been demonstrated but have been used along the years and are responsible for the success that this theory has had in explaining empirical economic phenomena.
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The TViews Table Role-Playing Game (TTRPG) is a digital tabletop role-playing game that runs on the TViews table, bridging the separate worlds of traditional role-playing games with the growing area of massively multiplayer online role-playing games. The TViews table is an interactive tabletop media platform that can track the location of multiple tagged objects in real-time as they are moved around its surface, providing a simultaneous and coincident graphical display. In this paper we present the implementation of the first version of TTRPG, with a content set based on the traditional Dungeons & Dragons rule-set. We also discuss the results of a user study that used TTRPG to explore the possible social context of digital tabletop role-playing games.
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Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2016
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The rise of a new leader of the state of Turkmenistan – President Gurbanguly Berdymukhammedov, who became ruler of the central Asian state after the 21-year rule of Saparmurad Niyazov, the self-proclaimed Turkmenbashi, who died on December 21, 2006 – has initiated changes in Turkmenistan’s political life. The new president has broken with the previous policy of self-isolation, and has directed the country towards openness to the outside world. Opportunities have thereby arisen for competitors in the ‘Great Game’, to gain political influence in Turkmenistan and access to hitherto unexploited Turkmen deposits of gas and oil. A new stage in the Great Game, which has been played for influence in Central Asia and control of access to its energy resources for many years, can thus be said to have been launched, and Turkmenistan has become the main setting for it. The major actors involved are Russia, the United States, China and the European Union.
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The Belarusian opposition is currently experiencing its deepest crisis since Alyaksandr Lukashenka took power in 1994. Following many months of negotiations, opposition leaders failed to select a joint candidate for the presidential election scheduled for 11th October. The failure of this latest round of talks has proven that not only is the opposition unlikely to threaten Lukashenka’s rule; it will not even be able to demonstrate to society that it could provide a genuine alternative to the present government.