A Semantic Navigation Model for Video Games

Driel, Leonard; Bidarra, Rafael

doi:10.1007/978-3-642-10347-6_14

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…They cover a vast set of rules expressing what the player can and cannot do and what the game can and cannot do to the player. It also includes the rewards and punishments [28]. The participating virtual entities include all objects, people, locations that form the game from walls and bricks to cities and maps and NPCs, such as monsters as well as a human opponent.…”

Section: Game Recognitionsupporting

confidence: 49%

“…This includes information on where objects are located in relation to each other and how movement action and limitations are portrayed in the game. Van Driel and Bidarra [28] suggest that game controls and navigation are at the core of a game environment. Game controls include information about how the player interacts with the game, where buttons are located on screen and how they affect game play for the player.…”

Section: Game Recognitionmentioning

confidence: 43%

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Personalise your massively multiplayer online game (MMOG) with Artemis

2011

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Better mobile computing, broadband and devices have contributed to the fast growth and popularity of massively multiplayer online games (MMOGs). Players are now expecting a more personalised gaming experience as personalisation has begun to filter into most games and not just MMOGs. In this paper, we explain how players of MMOGs can enjoy a ubiquitous and personalised gaming experience anywhere, on any device, and on any network with Artemis. MPEG-7 is not traditionally used for modelling games; however, Artemis adopts MPEG-7 for modelling the player, their device and the game, in conjunction with genetic algorithms for personalising the game, where possible.

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Section: Game Recognitionsupporting

confidence: 49%

Section: Game Recognitionmentioning

confidence: 43%

Personalise your massively multiplayer online game (MMOG) with Artemis

2011

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“…Modern gaming environments often confine the player to travel along clearly marked, programmed routes, meaning the player only has a limited number of ways in which they can proceed from location A to location B [16]. Embedded mechanisms can support innovative features such as geometric modification, enabling the players' actions to dynamically alter their environment to suit their style of play or abilities as they progress through the game.…”

Section: Lack Of Engagementsupporting

confidence: 43%

Action Recognition for Support of Adaptive Gameplay: A Case Study of a First Person Shooter

Kazmi

Palmer

2010

International Journal of Computer Games Technology

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With games continuously and rapidly evolving to become more complex and sophisticated in their nature and implementation. There is a fundamental need to sustain and deliver a similarly advanced, realistic, and engaging experience for the player. The implementation of "emergence" within games as providing an effective means to sustain this engagement in conjunction with some form of action recognition mechanism for its support. More recently, games have made much of the "adaptive" mechanisms that tailor the player experience during the game, but much of this appears to be implemented by merely making the game harder according to the success of the player. Some go further than this by incorporating adaptive AI that change agent tactics to suit the player's style of play. Whilst these are clearly advances in the approach to providing a player-centric experience to engage the player, the basis and transferability of these approaches is open to question. Here we propose a limited flavour of "emergence" which can be used to support an adaptive game mechanism and so present players with different gameplay experiences based on their actions within the game.

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“…They apply to the camera the navigation models that are used for the animation of autonomous non-player characters (Reese & Stout, 1999). Indirect approaches translate users needs into constraints on the camera parameters, which they intend to solve (Driel & Bidarra, 2009). …”

Section: Related Workmentioning

confidence: 45%