Behaviorally Modeling Games of Strategy Using Descriptive
نویسندگان
چکیده
Modeling human decision making in strategic problem domains is challenging with normative game theoretic approaches. Behavioral aspects of this type of decision making, such as forgetfulness or misattribution of reward, require additional parameters to capture their effect on decisions. We propose a descriptive model utilizing aspects of behavioral game theory, machine learning, and prospect theory that replicates the behavior of humans in uncertain strategic environments. We test the predictive capabilities of this model over data from 43 participants guiding a simulated Uninhabited Aerial Vehicle (UAV) against an unknown automated opponent. Modeling human decision making in strategic problem domains is challenging with normative game theoretic approaches. Behavioral aspects of this type of decision making, such as forgetfulness or misattribution of reward, require additional parameters to capture their effect on decisions. We propose a descriptive model utilizing aspects of behavioral game theory, machine learning, and prospect theory that replicates the behavior of humans in uncertain strategic environments. We test the predictive capabilities of this model over data from 43 participants guiding a simulated Uninhabited Aerial Vehicle (UAV) against an unknown automated opponent. Behaviorally Modeling Games of Strategy Using Descriptive Q-learning Roi Ceren Department of Computer Science University of Georgia Athens, GA 30605 [email protected] Prashant Doshi Department of Computer Science University of Georgia Athens, GA 30605 [email protected] Matthew Meisel Department of Psychology University of Georgia Athens, GA 30605 [email protected] Adam Goodie Department of Psychology University of Georgia Athens, GA 30605 [email protected] Dan Hall Department of Statistics University of Georgia Athens, GA 30605 [email protected]
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