Hoey, JesseJung, Joshua2016-10-252016-10-252016-10-252016http://hdl.handle.net/10012/11022Affect Control Theory (ACT), as a model of human interaction, attempts to capture a part of the human psyche that tends to go overlooked in the study of Artificial Intelligence: the role of emotion in decision making. It provides an empirically derived mathematical framework for the otherwise ethereal "feeling" that guide our every action, even in ways that may appear irrational. In this work, we apply BayesACT, a variant on classical ACT, to the much-studied Iterated Prisoner's Dilemma, showing that it appears to human players to approach the game more like a human than other computerized agents. Additionally, we expand into the networked version of this game, showing that the observed human behaviours of decision hysteresis, network structure invariance, and anti-correlation of cooperation and reward, are all emergent properties of the networked BayesACT agents.enPDcomputational social scienceaffect control theoryBayesACTNetworked Iterated Prisoner's Dilemmamultiagent systemsMaster Thesis