基于状态空间与概率空间映射的极大相似度匹配情感模型

机器人情感建模是研究情感机器人的热点问题。文中以情感心理学知识为基础，模拟具有不同个性的情感机器人在外界刺激作用下情感动态变化的过程，研究个性和外界刺激对情感转移过程的影响。采用基于状态空间的情感空间模型来描述机器人的情感状态，并用HMM过程来模拟情感状态的转移过程。但HMM过程只能求得当前情感状态的概率，为得到具体的情感状态，文中提出一种基于状态空间与概率空间映射的极大相似度匹配的情感转移模型。首先利用HMM过程计算出当前情感概率，然后通过极大相似度匹配来得到转移后具体的情感状态。通过调节模型参数来模拟不同个性和外界刺激，该模型能有效模拟情感状态变化过程。实验结果验证模型模拟的情感变化过程符合人类情感变化的一般规律。

Maximum Similarity Matching Emotion Model Based on Mapping between State Space and Probability Space

Robot emotion modeling is a hot issue in emotion robot research. Based on the emotion psychology knowledge,a dynamic emotion transfer model of the emotion robot is presented with different personalities under different external stimulation. The influences of personality and external stimulation are discussed. The emotion model based on state space is used to describe the emotion states of robot. The emotiontransfer process is simulated by hidden Markov model (HMM) process. However,the HMM process can only work out the current probability of the emotion state. To get the concrete emotion state,the maximum similarity matching emotion transfer model based on mapping between state space and probability space is proposed. Firstly,the current emotion probability is calculated by HMM process. Then,the current concrete emotion state is obtained by maximum similarity matching. Different personalities and stimulation can be built by adjusting the parameters of the model. The proposed model simulates the transformation process effectively. The experimental results show that the emotion transfer process simulated by the proposed model corresponds with the general rules of human emotion transformation.