Academic journal article International Review of Management and Business Research

Brain Activity Measurement in Gaming: Baming

Academic journal article International Review of Management and Business Research

Brain Activity Measurement in Gaming: Baming

Article excerpt

(ProQuest: ... denotes formulae omitted.)

Introduction

The study of games has been a major contributor to the gains in computer hardware and programming in recent decades, and to the body of knowledge of strategic decision-making for politics, finance, economics, games themselves, and many other fields. Game theory (GT) has provided a host of new topics and applications. Today GT is a multifarious hybrid science benefitting from the gains in programming and artificial intelligence (AI) which it helped to foment. Information science, neuroscience and evolutionary biology are a few of the fields to share in the bounties of game science. It is reasonable to expect valuable new insights from the continued study of games. Game Refinement Theory (GRT) considers the role of information complexity in the search space in games.

Claude Shannon began the age of computer gaming with a 1950 paper outlining a sample evaluation function for chess. What ensued was said to be the world's longest running computer experiment, ending in 1997 with the triumph of Deep Blue over Gary Kasparov. Because of its development with the computer chess problem, recreational game science was almost synonymous with AI in the latter half of the 20th century. Game Refinement Theory continues its expansion into the study of other games, like shogi, go, mah jhongg, and more recently into video games and sports. We hope this leads toward a workable general gaming model, which will be something analogous to strong AI in games. The present research is a small step in that direction. This paper explains Game Refinement Theory in the framework of traditional game theory, and points to the intersection of fNIRS brain measurement and games as an expanding field with excellent potential for game scientists. Prior studies have been carried out in the established frameworks of cognitive neuroscience or neurology. This group investigates games as forms of human and machine intelligence, for the purpose of understanding the fundamentals of games in general. The well-developed model of games as a vehicle of experimentation for cognitive neuroscientists is being established, and we recommend games for those engaged in brain studies, as with brain activity measurement for those in the research of AI and games.

Literature Review for Experimentation in Game Theory and Game Playing

Brain measurement experiments of players engaged in social dilemma and other economic games have been well underway for over a decade (Breiter et al., 2001; Rilling et al., 2002). Grether et al. (2007) contains a convincing call for functional brain experiments in economic games, which could be extended to recreational games as reasonable proxies, if not direct measurements, of general game behaviour. Functional brain activity measurement of players during gaming (BAMING) has begun to show some benefits in several related fields. Since the beginning of the new millennium, findings from BAMING have led to better models of cognition, deeper understanding of social behaviour, more and better maps of human brain connectivity and function, and improved methods and analytics. A few mentionable works include the subjects of brain measurements during currency auctions (Grether et al., 2007), reciprocity in the context of social dilemmae (Nagatsuka, Shinagawa, Okano, Kitamura & Saijo, 2013; Rilling et al., 2002), the ability of players to perform under stress (Izzetoglu, Bunce, Onarel, Pourrezaei & Chance, 2004), and various recreational gaming functional brain studies, like (Mathiak et al., 2011, Matsuda & Hiraki, 2006; Saito, Mukawa & Saito, 2007). There are implications for these advancements in brain-to-machine interfaces, affective gaming, neural connectivity studies, and research on the disabled, to name a few (Hoshi et al., 2011; Matthews, Pearlmutter, Ward, Soraghan & Markham, 2008; Ono et al., 2014; Tan & Nijholt 2010; Tachtsidis & Papaioannou 2013; Volz, Schubotz & von Cramon, 2005). …

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