Adaptive Game AI-Based Dynamic Difficulty Scaling via the Symbiotic Game Agent

Abstract

This work presents AdaptiveSGA, a model for implementing Dynamic Difficulty Scaling through Adaptive Game AI via the Symbiotic Game Agent framework. The use of Dynamic Difficulty Balancing in modern computer games is useful when looking to improve the entertainment value of a game. Moreover, the Symbiotic Game Agent, as a framework, provides flexibility and robustness as a design principle for game agents. The work presented here leverages both the advantages of Adaptive Game AI and Symbiotic Game Agents to implement a robust, efficient and testable model for game difficulty scaling. The model is discussed in detail and is compared to the original Symbiotic Game Agent architecture. Finally, the paper describes how it was applied in simulated soccer. Finally, experimental results, which show that Dynamic Difficulty Balancing was achieved, are briefly analyzed.

The application of artificial intelligence technology in game design

“…As a result, game characters can be adaptively adjusted without interruption. Building upon the symbiotic game agent model, the AdaptiveSGA model is proposed to achieve adaptive game artificial intelligence for dynamic difficulty balancing by manipulating character behavior [3]. In Figure 1, "Red Dead Redemption 2" utilizes deep reinforcement learning strategies, where the environment serves as a driving background for the agent's actions, and a trained neural policy network autonomously generates corresponding actions, resulting in unpredictable behavior for each character.…”

“…Artificial intelligence technology can not only bring more realistic and rich game experiences to players, but also provide personalized and customized game plots and gameplay for each player, increasing player engagement and loyalty. It is evident that artificial intelligence technology plays an important role in the field of game design [2][3][4]. This paper will focus on the application of artificial intelligence technology in game design from three aspects.…”