Narrative Review of Game AI 2000 Onwards and Future Research Directions

The purpose of the chapter is to structure and synthesize the research findings in Gaming AI till date by reviewing the research articles published in high citation, indexed, and peer reviewed journals. Eighteen articles were extracted through systematic process of search and exclusion and inclusion criteria adopted for the study. The selected papers were categorized according to the simulation for AI and AI-based simulation model, and AI applications from literature was reviewed, and conclusions were drawn. Research in Gaming AI is fragmented and unrelated as regards geographical, methodological, and disciplinary aspects. Gaming AI is an emerging research area which is gaining interest in recent years though very little quantitative or qualitative research has been undertaken till date. Recommendations on future research directions were made.

Team Sports for Game AI Benchmarking Revisited

Sport games are among the oldest and best established genres of computer games. Sport-inspired environments, such as RoboCup, have been used for AI benchmarking for years. We argue that, in spite of the rise of increasingly more sophisticated game genres, team sport games will remain an important testbed for AI benchmarking due to two primary factors. First, there are several genre-specific challenges for AI systems that are neither present nor emphasized in other types of games, such as team AI and frequent replanning. Second, there are unmistakable nonskill-related goals of AI systems, contributing to player enjoyment, that are most easily observed and addressed within a context of a team sport, such as showing creative and emotional traits. We analyze these factors in detail and outline promising directions for future research for game AI benchmarking, within a team sport context.