Co-creative AI research increasingly seeks methods capable of representing how interaction dynamics evolve through time. While many existing approaches focus on observable interaction characteristics, interaction metrics, behavioral coding schemes, or activity traces, these methods often struggle to capture higher-order interaction dynamics, including how collaborative processes reorganize, stabilize, regulate, and evolve through time. This paper introduces Cognitive Trajectory Modeling (CTM) as a cognitive theory of interaction dynamics that conceptualizes cognition, interaction, and creative processes as temporally organized trajectories unfolding across cognitively meaningful attractor landscapes. CTM builds upon the theoretical foundations of the Enactive Model of Creativity and Creative Sense-Making (CSM), revisiting the role of sense-making curves and cognitive trajectories in representing co-creative interaction dynamics. We formalize this perspective through the Cognitive Trajectory Principle, which states that temporal representations are only theoretically interpretable as cognitive trajectories when their underlying states possess directional cognitive meaning. Building on this principle, CTM generalizes the notion of cognitive trajectories beyond any particular coding scheme and provides a broader framework for modeling interaction dynamics through trajectories unfolding across meaningful attractor landscapes. We further distinguish cognitive trajectories from interaction traces and situate CTM within a broader hierarchy of cognitive, interaction, and domain dynamics. More broadly, we argue that understanding co-creative systems requires methods capable of modeling how cognition and interaction dynamics unfold through time. CTM provides a foundation for studying interaction dynamics across co-creative AI and human-AI interaction.

翻译：协同创造性AI研究日益寻求能够表征交互动态随时间演变的方法。尽管现有许多方法聚焦于可观测的交互特征、交互度量、行为编码方案或活动痕迹，但这些方法往往难以捕捉高阶交互动态，包括协作过程如何随时间重组、稳定、调节和演变。本文提出认知轨迹建模（CTM），将其作为一种关于交互动态的认知理论，该理论将认知、交互和创造过程概念化，视为在具有认知意义的吸引子景观中展开的、在时间上组织的轨迹。CTM建立在创造性生成模型与创造性意义建构（CSM）的理论基础之上，重新审视了意义建构曲线和认知轨迹在表征协同创造交互动态中的作用。我们通过认知轨迹原则形式化这一视角，该原则指出，只有当时间表征的底层状态具备方向性的认知意义时，这些表征才在理论上可被解释为认知轨迹。基于这一原则，CTM将认知轨迹的概念泛化至任何特定编码方案之外，并提供了一个更广泛的框架，用于通过在有意义的吸引子景观中展开的轨迹来建模交互动态。我们进一步将认知轨迹与交互痕迹区分开来，并将CTM置于更广泛的认知、交互和领域动态层级结构中。更广泛而言，我们认为理解协同创造系统需要能够建模认知和交互动态如何随时间展开的方法。CTM为跨协同创造AI和人类-AI交互的交互动态研究奠定了基础。