Characterizing robustness of strategies to novelty in zero-sum open worlds

Introduction: In open-world environments, artificial agents must often contend with novel conditions that deviate from their training or design assumptions. This paper studies the robustness of fixed-strategy agents to such novelty in two-player competitive settings. Materials and methods: We present a general framework for characterizing the impact of environmental novelties, such as changes in payoff structure or action constraints, on agent performance in two domains: Iterated Prisoner’s Dilemma (IPD) and heads-up Texas Hold’em Poker. Novelty is operationalized as a perturbation of the game’s rules or scoring mechanics, while agent behavior remains fixed. To measure the effects, we introduce two metrics: per-agent robustness, summarizing post-novelty tournament performance across opponents, and global impact, summarizing the population-wide disruption caused by a novelty. Experiments comprise 30 IPD agents across 20 payoff-matrix novelties and 10 Poker agents across 5 rule-based novelties. Results: The experiments reveal systematic variation in robustness across both domains. In IPD, several novelties produce severe population-wide disruption, while others have near-zero impact because they preserve the strategic ordering of the game. In Poker, brittleness is concentrated in a smaller subset of simple heuristic agents, while more conservative or stochastic agents remain comparatively stable under the evaluated novelties. The results support the interpretation that robustness under novelty depends not only on absolute performance but also on whether the governing rules preserve, erase, or invert the strategic assumptions encoded in a policy. Conclusions: The study provides an exploratory, cross-domain methodology for quantifying how fixed strategies respond to novelty and offers a quantitative basis for future work on safer and more resilient autonomous systems in adversarial and dynamic environments.