997 resultados para Game Jams


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The studio-gameon event was supported by the Institute of the Creative Industries and Innovation and the Faculty of IT as part of the State Library of Queensland GAME ON exhibition (ex Barbican, UK) The studio produced a full game in six weeks. It was a curated event, a live web-based exhibition, a performance for the public and the team produced a digital / creative work which is available for download. The studio enabled a team of students to experience the pressures of a real game studio within the space of the precincts but also very much in the public eye. It was a physical hypothesis of the University's mantra - "for the real world" statement: Studio GameOn is an opportunity running alongside the GAME ON exhibition at the State Library of Queensland. The exhibition itself is open to the public from November 17th through to February 15th. The studio runs from January 5th to February 13th 2009. The Studio GameOn challenge? To put together a team of game developers and make a playable game in six weeks! The studio-game on team consists of a group of game developers in training - the team members are all students who are either half-way through or completing a qualification in game design and all its elements - we have designers, artists, programmers and productionteam members. We are also fortunate to have an Industry Board consisting of local Queensland Games professionals: John Passfield (Red Sprite Studios), Adrian Cook (WIldfire Studios) and Duncan Curtis and Marko Grgic (The 3 Blokes). We also invite the public to play with us - there is an ideas box both on-site at the State Library and a number of ways to communicate with us on this studio website.

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The 48 hour game making challenge has been running since its inception at the NEXT LEVEL Festival in 2004. It is curated by Truna aka j. Turner and Lubi Thomas and sees teams of both future game makers and industry professionals going head to head under pressure to produce playable games within the time period. The 48 hour is supported by the International Game Developers Association (Brisbane Chapter)and the Creative Industries Precincts as part of their public programs. It is a curated event which engages industry with Brisbane educational institutes and which fosters the Australian Games Industry

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This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.

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One of the main aims in artificial intelligent system is to develop robust and efficient optimisation methods for Multi-Objective (MO) and Multidisciplinary Design (MDO) design problems. The paper investigates two different optimisation techniques for multi-objective design optimisation problems. The first optimisation method is a Non-Dominated Sorting Genetic Algorithm II (NSGA-II). The second method combines the concepts of Nash-equilibrium and Pareto optimality with Multi-Objective Evolutionary Algorithms (MOEAs) which is denoted as Hybrid-Game. Numerical results from the two approaches are compared in terms of the quality of model and computational expense. The benefit of using the distributed hybrid game methodology for multi-objective design problems is demonstrated.

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This paper presents the application of advanced optimization techniques to unmanned aerial system mission path planning system (MPPS) using multi-objective evolutionary algorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEA nondominated sorting genetic algorithm II and a hybrid-game strategy are implemented to produce a set of optimal collision-free trajectories in a three-dimensional environment. The resulting trajectories on a three-dimensional terrain are collision-free and are represented by using Bézier spline curves from start position to target and then target to start position or different positions with altitude constraints. The efficiency of the two optimization methods is compared in terms of computational cost and design quality. Numerical results show the benefits of adding a hybrid-game strategy to a MOEA and for a MPPS.

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In this paper, the optimal design of an active flow control device; Shock Control Bump (SCB) on suction and pressure sides of transonic aerofoil to reduce transonic total drag is investigated. Two optimisation test cases are conducted using different advanced Evolutionary Algorithms (EAs); the first optimiser is the Hierarchical Asynchronous Parallel Evolutionary Algorithm (HAPMOEA) based on canonical Evolutionary Strategies (ES). The second optimiser is the HAPMOEA is hybridised with one of well-known Game Strategies; Nash-Game. Numerical results show that SCB significantly reduces the drag by 30% when compared to the baseline design. In addition, the use of a Nash-Game strategy as a pre-conditioner of global control saves computational cost up to 90% when compared to the first optimiser HAPMOEA.

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Over recent years, Unmanned Air Vehicles or UAVs have become a powerful tool for reconnaissance and surveillance tasks. These vehicles are now available in a broad size and capability range and are intended to fly in regions where the presence of onboard human pilots is either too risky or unnecessary. This paper describes the formulation and application of a design framework that supports the complex task of multidisciplinary design optimisation of UAVs systems via evolutionary computation. The framework includes a Graphical User Interface (GUI), a robust Evolutionary Algorithm optimiser named HAPEA, several design modules, mesh generators and post-processing capabilities in an integrated platform. These population –based algorithms such as EAs are good for cases problems where the search space can be multi-modal, non-convex or discontinuous, with multiple local minima and with noise, and also problems where we look for multiple solutions via Game Theory, namely a Nash equilibrium point or a Pareto set of non-dominated solutions. The application of the methodology is illustrated on conceptual and detailed multi-criteria and multidisciplinary shape design problems. Results indicate the practicality and robustness of the framework to find optimal shapes and trade—offs between the disciplinary analyses and to produce a set of non dominated solutions of an optimal Pareto front to the designer.

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Authorised users (insiders) are behind the majority of security incidents with high financial impacts. Because authorisation is the process of controlling users’ access to resources, improving authorisation techniques may mitigate the insider threat. Current approaches to authorisation suffer from the assumption that users will (can) not depart from the expected behaviour implicit in the authorisation policy. In reality however, users can and do depart from the canonical behaviour. This paper argues that the conflict of interest between insiders and authorisation mechanisms is analogous to the subset of problems formally studied in the field of game theory. It proposes a game theoretic authorisation model that can ensure users’ potential misuse of a resource is explicitly considered while making an authorisation decision. The resulting authorisation model is dynamic in the sense that its access decisions vary according to the changes in explicit factors that influence the cost of misuse for both the authorisation mechanism and the insider.

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The present paper focuses on some interesting classes of process-control games, where winning essentially means successfully controlling the process. A master for one of these games is an agent who plays a winning strategy. In this paper we investigate situations in which even a complete model (given by a program) of a particular game does not provide enough information to synthesize—even incrementally—a winning strategy. However, if in addition to getting a program, a machine may also watch masters play winning strategies, then the machine is able to incrementally learn a winning strategy for the given game. Studied are successful learning from arbitrary masters and from pedagogically useful selected masters. It is shown that selected masters are strictly more helpful for learning than are arbitrary masters. Both for learning from arbitrary masters and for learning from selected masters, though, there are cases where one can learn programs for winning strategies from masters but not if one is required to learn a program for the master's strategy itself. Both for learning from arbitrary masters and for learning from selected masters, one can learn strictly more by watching m+1 masters than one can learn by watching only m. Last, a simulation result is presented where the presence of a selected master reduces the complexity from infinitely many semantic mind changes to finitely many syntactic ones.

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This study explores the effects of use-simulated and peripheral placements in video games on attitude to the brand. Results indicate that placements do not lead to enhanced brand attitude, even when controlling for involvement and skill. It appears this is due to constraints on brand information processing in a game context.

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This full day workshop invites participants to consider the nexus where the interests of game design, the expectations of play and HCI meet: the game interface. Game interfaces seem different to the interface to other software and there have been a number of observations. Shneiderman famously noticed that while most software designers are intent on following the tenets of the “invisible computer” and making access easy for the user, games inter-faces are made for players: they embed challenge. Schell discusses a “strange” relationship between the player and the game enabled by the interface and user interface designers frequently opine that much can be learned from the design of game interfaces. So where does the game interface actually sit? Even more interesting is the question as to whether the history of the relationship and sub-sequent expectations are now limiting the potential of game design as an expressive form. Recent innovations in I/O design such as Nintendo’s Wii, Sony’s Move and Microsoft's Kinect seem to usher in an age of physical player-enabled interaction, experience and embodied, engaged design. This workshop intends to cast light on this often mentioned and sporadically examined area and to establish a platform for new and innovative design in the field.

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The aim of this project was to implement a just-in-time hints help system into a real time strategy (RTS) computer game that would deliver information to the user at the time that it would be of the most benefit. The goal of this help system is to improve the user’s learning in terms of their rate of learning, retention and avoidance of stagnation. The first stage of this project was implementing a computer game to incorporate four different types of skill that the user must acquire, namely motor, perceptual, declarative knowledge and strategic. Subsequently, the just-in-time hints help system was incorporated into the game to assess the user’s knowledge and deliver hints accordingly. The final stage of the project was to test the effectiveness of this help system by conducting two phases of testing. The goal of this testing was to demonstrate an increase in the user’s assessment of the helpfulness of the system from phase one to phase two. The results of this testing showed that there was no significant difference in the user’s responses in the two phases. However, when the results were analysed with respect to several categories of hints that were identified, it became apparent that patterns in the data were beginning to emerge. The conclusions of the project were that further testing with a larger sample size would be required to provide more reliable results and that factors such as the user’s skill level and different types of goals should be taken into account.