Co-creative collaboration is a creative collaboration of two or more agents working together on a shared creative product. Effective co-creative collaboration is a combination of interactions and contributions of the task collaborators. In human-human collaboration, gestures, verbal communications, and emotional responses are among the general communication strategies that shape the interactions between the collaborators and enable negotiation of the contributions. Emotional feedback allows human collaborators to passively communicate their stance about the experience and convey their perception of the process without distracting the flow of the task. In human-human co-creative collaboration, participants interact and contribute to the task based on their perception of the collaboration over time. However, perceiving the cognitive state of the user to determine the dynamics of collaboration and decide what the agent should contribute to the artifact are two primary challenges of building effective co-creative Artificial Intelligence systems (Abdellahi et all, 2020). In response to these two challenges, the following thesis statement is presented:Using knowledge of human emotion in human-AI co-creative collaboration can improve the user satisfaction of the collaboration experience and quality of the collaboration outcome. This thesis focuses on establishing dynamics of co-creative collaboration between a human and a co-creative AI agent through an emotion-based interaction model for co-creativity. After the introduction in chapter 1 and reviewing the related background in chapter 2, the 3rd chapter of this dissertation presents an interaction model for Arny V1, a co-creative system designed to explore the research questions of this thesis. Arny V1 interaction model was studied as part of an exploratory study with the Wizard of Oz setup that is discussed in chapter 4 of this document. The modified version of the model, Arny V2, was then deployed and analyzed to confirm the thesis statement, as well as identify possible improvements. Studies of Arny V1 and Arny V2 confirmed this dissertation's thesis statement that consideration of affect in human AI creative collaboration can improve the satisfaction of the experience as well as the quality of the outcome. This research also identified valence and engagement as two emotion dimensions beneficial for designing affective co-creative AI agents.