Abstract In recent years,the Belief-Desire-Intention model is one of the most influential theories with respect to agent technology. Propositional dynamic logic and the infinite-valued ukasiewicz logic are blended to formulize the emotional graded BDI model. In order to represent the uncertainty behaviors by belief,desire,intention,fear,anxiety and self-confidence degree,the corresponding axioms are added to the ukasiewicz logic. The proposed emotional graded BDI agent model explicitly represents the uncertainty of mental attitudes and emotional states. The behavior of emotional graded BDI agent is determined by the different measure of each context which is added by concrete conditions. The model of beliefs,desires,intentions,fear,anxiety and self-confidence are axiomatized,and how they influence the behavior of agent is shown. This model is general enough to specify different types of agents. On the basis of presenting the language and semantics for this model,the axioms and rules are proposed for the emotional graded BDI logic and the dependability and completeness of the logic are proved. After illustrating the interrelations between different contexts for the model,an application of an emotional graded BDI agent for purchasing houses is given. Aiming at the representation and reasoning for the uncertainty,a formal support for distributed artificial intelligence is provided.
[1]Cai Zixing,Xu Guangyou. Artificial Intelligence: Principles and Applications. 4th Edition. Beijing,Chinese: Tsinghua University Press,2010: 208-209 (in Chinese)（蔡自兴,徐光佑.人工智能及其应用.第4版.北京：清华大学出版社,2010: 208-209） [2]Steunebrink B R,Dastani M,Meyer J J C. A Formal Model of Emotion Triggers: An Approach for BDI Agents. Synthese,2011,185(1): 83-129 [3]Liu Gang,Zheng Li,Sun Yuanyun,et al. Forming Mechanism of BDI Agent Based on Activity and Its Application. Journal of Central South University: Science and Technology,2009,40(S1): 25-28 (in Chinese)（刘 刚,郑 力,孙远远,等.基于活动的BDI主体形成机制及应用.中南大学学报:自然科学版,2009,40(S1): 25-28） [4]Chen Zhongxiang. Theoretical and Technical Research on the CGF Behavioral Modeling Based on BDI Agent. Ph.D Dissertation. Wuhan,China: Huazhong University of Science and Technology,2004 (in Chinese)（陈中祥.基于BDI Agent的CGF主体行为建模理论与技术研究.博士论文.武汉,中国：华中科技大学,2004） [5]Meyer J J C. Reasoning about Emotional Agents // Proc of the 16th European Conference on Artificial Intelligence. Amsterdam,Netherlands,2004: 129-133 [6]Pereira D,Oliveira E,Moreira N. Modeling Emotional BDI Agents // Proc of the Workshop on Formal Approaches to Multi Agent Systems. Riva Del Garda, Italy,2006: 1-13 [7]Pereira D,Oliveria E,Moreira N. Formal Modeling of Emotions in BDI Agents // Sadri F,Satoh K,eds. Computational Logic in Multi Agent Systems. Berlin,Germany: Springer Verlag,2008: 62-81 [8]Rao A S,Georgeff M P. Modeling Rational Agents within a BDIArchitecture // Proc of the 2nd International Conference on Principles of Knowledge Representation and Reasoning. Cambridge,USA,1991: 473-484 [9]Rao A S,Georgeff M P. Decision Procedures for BDI Logics. Journal of Logic and Computation,1998,8(3): 293-342 [10]Van der Hoek W,Van Linder B,Meyer J J. On Agents That Have the Ability to Choose. Studia Logica,2000,66(1): 79-119 [11]Casali A,Godo L,Sierra C. Graded BDI Models for Agent Architectures // Proc of the 5th International Workshop on Compu tational Logic in Multi Agent Systems. Lisbon,Portugal,2005: 126-143 [12]Zhang Xiaojun,Jiang Min,Zhou Changle,et al.Graded BDI Models for Agent Architectures Based on ukasiewicz Logic and Propositional Dynamic Logic // Proc of the International Conference on Web Information Systems and Mining. Chengdu,China,2012,439-50 [13]Harel D,Kozen D,Tiuryn J. Dynamic Logic. Cambridge,USA: The MIT Press,2000: 163-173 [14]Hájek P. Mathematics of Fuzzy Logic. Dordrecht,Netherlands: Kluwer Academic Publishers,1998: 63-79 [15]Blackburn P,de Rijke M,de Venema Y. Modal Logic. Cambridge,UK: Cambridge University Press,2002: 46-49 [16]Liau C J. Belief,Information Acquisition and Trust in Multiagent Systems A Modal Logic Formulation. Artificial Intelligence,2003 149(1): 31-60
2013, Vol. 26 
