Serious games have drawn attention with positive effects on users in various areas. While many categorizations and definitions of serious games have attempted to elucidate the elusive term, we are still some way off in formulating an agreed understanding of what serious games are and how they can be classified. This paper aims to provide an overall picture of the concepts and categorizations of serious games. From the results of previous literature, the major applications of serious games can be converged into five primary areas: public policy, military, education, corporate and healthcare. Likewise, theories applied to serious games comprise three main strategic purposes: information notification/PR, change of user attitude/behavior, and purposive training. Based on the strategic purposes and applied areas, this study categorizes serious games into 15 sectors. In addition, founded on the motivation factors and the characteristics of digital games, the current study suggests a new definition of serious games.

Recently, simultaneous localization and mapping (SLAM) approaches employing Rao-Blackwellized particle filter (RBPF) have shown good results. However, due to the usage of the accurate sensors, distinct particles which compensate one another are attenuated as the RBPF-SLAM continues. To avoid this particle depletion, we propose the strategic games to assign the particle’s payoff which replaces the importance weight in the current RBPF-SLAM framework. From simulation works, we show that RBPF-SLAM with the strategic games is inconsistent in the pessimistic way, which is different from the existing optimistic RBPF-SLAM. In addition, first, the estimation errors with applying the strategic games are much less than those of the standard RBPF-SLAM, and second, the particle depletion is alleviated.