Interacting with an artificial partner: modeling the role of emotional aspects.
In this paper we introduce a simple model based on probabilistic finite state automata to describe an emotional interaction between a robot and a human user, or between simulated agents. Based on the agent's personality, attitude, and nature, and on the emotional inputs it receives, the model will determine the next emotional state displayed by the agent itself. The probabilistic and time-varying nature of the model yields rich and dynamic interactions, and an autonomous adaptation to the interlocutor. In addition, a reinforcement learning technique is applied to have one agent drive its partner's behavior toward desired states. The model may also be used as a tool for behavior analysis, by extracting high probability patterns of interaction and by resorting to the ergodic properties of Markov chains.
Cattinelli
Isabella
I
Applied Intelligent Systems Laboratory, Department of Computer Science, Università degli Studi di Milano, Via Comelico 39/41, 20135, Milan, Italy. cattinelli@dsi.unimi.it
Goldwurm
Massimiliano
M
Borghese
N Alberto
NA
D001185:Artificial Intelligence; D001525:Behavioral Sciences / Q000379:methods; D004644:Emotions; D006801:Humans; D008390:Markov Chains; D016571:Neural Networks, Computer; D012054:Reinforcement, Psychology; D012371:Robotics / Q000379:methods*; D012919:Social Behavior; D014584:User-Computer Interface