Paper Info
Title
A Probabilistic Approach to Represent Emotions Intensity into BDI Agents.
Abstract
The BDI (Belief-Desire-Intention) model is a well known reasoning architecture for intelligent agents. According to the original BDI approach, an agent is able to deliberate about what action to do next having only three main mental states: belief, desires and intentions. A BDI agent should be able to choose the more rational action to be done with bounded resources and incomplete knowledge in an acceptable time. As humans need emotions to make immediate decisions with incomplete information, some recent works have extending the BDI architecture in order to integrate emotions. However, as they only use logic to represent emotions, they are not able to define the intensity of the emotions. In this paper we present an implementation of the appraisal process of emotions into BDI agents using a BDI language that integrates logic and probabilistic reasoning. Hence, our emotional BDI implementation allows to differentiate between emotions and affective reactions. This is an important aspect because emotions tend to generate stronger response. Besides, the emotion intensity also determines the intensity of an individual reaction. In particular, we implement the event-based emotions with consequences for self based on the OCC cognitive psychological theory of emotions. We also present an illustrative scenario and its implementation.
Year
DOI
Venue
2014
10.1007/978-3-319-25210-0_14
AGENTS AND ARTIFICIAL INTELLIGENCE, ICAART 2014
Keywords
Field
DocType
BDI,Emotions,Appraisal,OCC,Bayesian decision networks,BDN
Incomplete knowledge,Intelligent agent,Computer science,Cognitive psychology,Artificial intelligence,Probabilistic logic,Cognition,Affect (psychology),Psychological Theory,Machine learning,Complete information
Conference
Volume
ISSN
Citations 
8946
0302-9743
0
PageRank 
References 
Authors
0.34
9
2
Name
Order
Citations
PageRank
João Carlos Gluz1135.84
Patrícia Augustin Jaques210515.88