Argumentation games, which model reasoning as adversarial dialogue, offer intuitive and explainable mechanisms for decision-making in AI. However, their implementation has lagged behind inference-focused approaches, particularly in structured argumentation frameworks like assumption-based argumentation (ABA). This work presents, to our knowledge, the first application of multi-shot answer set programming (ASP) for implementing argument games, focusing on ABA dispute derivations. Leveraging a recent rule-based representation of ABA disputes, our method combines a declarative program with lightweight script-based control of multi-shot aspects, yielding a modular and adaptable system. We extend this core approach to support alternative games and show how it can also be used to implement argument games for Dung’s abstract argumentation formalism. Empirical results show that our implementation outperforms existing ABA dispute systems. We also introduce an approximate variant that further improves efficiency – reaching the level of the best inference-focused ABA system – while maintaining perfect specificity (true negative rate), demonstrating the practical value of multi-shot ASP, especially in interactive, explainable settings.