This paper outlines a software framework for the simulation of dynamic emotions in simulated agents. This framework acts as a domain-independent, black-box solution for giving actors in games or simulations realistic emotional reactions to events. The emotion management engine provided by the framework uses a modified Fuzzy Logic Adaptive Model of Emotions (FLAME) model, which lets it manage both appraisal of events in relation to an individual’s emotional state, and learning mechanisms through which an individual’s emotional responses to a particular event or object can change over time. In addition to the FLAME model, the engine draws on the design of the GAMYGDALA emotional engine for games. Evaluations of the model’s behavior over a set of test cases are performed, with a discussion of the model’s efficacy in different situations.
Code, Douglas, "Learning Emotions: A Software Engine for Simulating Realistic Emotion in Artificial Agents" (2015). Senior Independent Study Theses. Paper 6543.
Artificial Intelligence and Robotics | Computational Neuroscience | Theory and Algorithms
Bachelor of Arts
Senior Independent Study Thesis Exemplar
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