Formalization of Event Perception and Event Appraisal Process

Integration of emotion in a virtual agent is a topic of research to depict human-like behavior in a simulated environment. For the last few decades, many researchers are working in the field of incorporating emotions in a virtual agent. In the emotion model, the behavior of an agent depends upon how the event is perceived by the agent with respect to the goal. Hence, perception of the event while considering the past experience, importance of event towards achieving goal, agent�s own capabilities and resources is an important process which directly influences the decision making and action selection. The proposed models, till date, are either too complex to adapt or are using a very few parameters to describe the event. So, in this paper, we propose an extension of perception process in an existing emotion model, EMIA and suggest the formalization of event perception and appraisal processes to make it adaptable. This has been carried out using five parameters for event description along-with fuzzy logic which makes the process more effective yet simple.

[1]  Abhishek Vaish,et al.  Instant Human Face Attributes Recognition System , 2011 .

[2]  Shikha Jain,et al.  EmET: Emotion Elicitation and Emotion Transition Model , 2015 .

[3]  Shikha Jain,et al.  EMIA: Emotion Model for Intelligent Agent , 2015, J. Intell. Syst..

[4]  Stacy Marsella,et al.  A domain-independent framework for modeling emotion , 2004, Cognitive Systems Research.

[5]  Andrew Ortony,et al.  The Cognitive Structure of Emotions , 1988 .

[6]  Jordán Pascual Espada,et al.  Machine learning approach for text and document mining , 2014, ArXiv.

[7]  Ignasi Iriondo Sanz,et al.  Comparative Study on Feature Selection and Fusion Schemes for Emotion Recognition from Speech , 2012, Int. J. Interact. Multim. Artif. Intell..

[8]  Ira J. Roseman,et al.  Appraisals of emotion-eliciting events: Testing a theory of discrete emotions. , 1990 .

[9]  Eva Hudlicka Modeling Effects of Behavior Moderators on Performance: Evaluation of the MAMID Methodology and Architecture , 2015 .

[10]  Dominique Duhaut,et al.  GRACE – GENERIC ROBOTIC ARCHITECTURE TO CREATE EMOTIONS , 2008 .

[11]  Parismita Sarma,et al.  A Machine Learning Approach for Text and Document Mining , 2017 .

[12]  Abhishek Vaish,et al.  Brainwave based user identification system: A pilot study in robotics environment , 2015, Robotics Auton. Syst..

[13]  John Yen,et al.  FLAME—Fuzzy Logic Adaptive Model of Emotions , 2000, Autonomous Agents and Multi-Agent Systems.

[14]  Mehdi Dastani,et al.  Agents with emotions , 2010, Int. J. Intell. Syst..

[15]  K. Scherer Emotion as a multicomponent process: A model and some cross-cultural data. , 1984 .

[16]  Krishna Asawa,et al.  Recognition of Emotions using Energy Based Bimodal Information Fusion and Correlation , 2014, Int. J. Interact. Multim. Artif. Intell..

[17]  Michael N. Huhns,et al.  EBDI: an architecture for emotional agents , 2007, AAMAS '07.

[18]  P. Ekman An argument for basic emotions , 1992 .

[19]  Rubén González Crespo,et al.  Patterns of Software Development Process , 2011, Int. J. Interact. Multim. Artif. Intell..

[20]  Shikha Jain,et al.  EmoXract: Domain independent emotion mining model for unstructured data , 2014, 2014 Seventh International Conference on Contemporary Computing (IC3).

[21]  Abhishek Vaish,et al.  Feature extraction using emprical mode decomposition for biometric system , 2014, 2014 International Conference on Signal Propagation and Computer Technology (ICSPCT 2014).

[22]  Abhishek Vaish,et al.  Brainwave's energy feature extraction using wavelet transform , 2014, 2014 IEEE Students' Conference on Electrical, Electronics and Computer Science.