# Contextual Emotion Appraisal Based on a Sentential Cognitive System for Robots
## 5 Experiments and Results
### Experimental Results
In the case of S\({}_{4}\) and S\({}_{6}\), a user (A\({}_{1}\)) as an agent did the positive action to the robot, but the other user (A\({}_{2}\)) did the negative in the events of S\({}_{14}\) to S\({}_{20}\). Table 7 shows the sentential memory of each event with the emotional valence, which was obtained from the emotional appraisal system. Events that occurred with agents and objects in front of the robot were stored in the sentential memory with chronological order. In the case of S\({}_{1}\)–S\({}_{3}\) and S\({}_{11}\)–S\({}_{13}\), new agents, A\({}_{1}\) and A\({}_{2}\), appeared, and the robot had a neutral emotional valence to them at first. Figure 9: The variation of emotion appraisal toward the agents (A\({}_{1}\) and A\({}_{2}\)). JD_E. GA_A\({}_{1}\) was sustained for the time being and decreased with the graphical form of GA_A in Figure 7. Because GA_A\({}_{1}\) was over a threshold value (0.5) with a new event of bringing a fruit, the robot remarked \"Thank you [PERSON]\" to the agent A\({}_{1}\), like (S\({}_{5}\), S\({}_{7}\)). With the appearance of an orange (a priori LH valence: 0.3), the valence of GA_A\({}_{1}\) was over the threshold value (\(T_{k}\): 0.6), which made an emotional transition to LH_A\({}_{1}\) with a weight factor (\(h_{k}\): 0.8) of (4). Because LH_A\({}_{1}\) was over the threshold value (0.5) with a new event, the robot uttered \"I love you [PERSON]\" to the agent A\({}_{1}\) (S\({}_{8}\)). When an agent A\({}_{2}\) brought fruits having negative a priori LH_O valences, or took away the liked fruits, the GA_A\({}_{2}\) had negative values and expressed negative utterances, such as \"I am angry [PERSON]\" (S\({}_{16}\), S\({}_{18}\), S\({}_{21}\)). The negative valence of GA_A\({}_{2}\) also made an emotional transition to LH_A\({}_{2}\) with the same \(T_{k}\) (0.5) (S\({}_{17}\)) and the utterance of \"I hate you [PERSON]\" (S\({}_{19}\)). In Figure 9, we can see that the valence of GA_A\({}_{2}\) decreased to neutral in a short time whereas the valence of LH_A\({}_{2}\) sustained longer by adopting the parameters of \(E(t)\) in Table 6, like the graphical characteristics of each emotion as shown in Figure 7. In the case of PS_E, it was developed by the event the robot did itself. For example, if the robot fails to pick up an apple when it is normal to pick it up, it will produce PS_E valence. In this experiment, this kind of event did not happen, and all of the valences of PS_E were 0.0. Figure 10 shows the variations of emotion appraisal toward all events over time. There were multiple events, such as the appearance and disappearance of fruits, and the love and hate events to agents. The JD_E of the robot was appraised by the combinational transitions of LH_O (Figure 3,3) and LH_A (Figure 3,5) according to Equation (4). The transition from LH_O was computed by summation of the positive and negative events with the emotional combination rate (0.9) when the robot encountered the fruits, and the transition from LH_A was calculated with the integration of positive and negative LH_A. The JD_E was positive at first, but converted to negative at the time of 10:17:32 (S\({}_{15}\)). When it was predicted that the target of H_A1 would appear in the future with \"See you tomorrow (S\({}_{9}\)),\" the transition from LH_A (Figure 3,6) to HF_E happened at first with \(T_{k}\) (0.5) and \(h_{k}\) (0.8). When the robot heard the same sentence from A2, the valence of HF_E switched to negative and gradually shifted to neutral value. These experiments demonstrated contextual emotion appraisal in multiple points of view. First, the proposed contextual appraisal system showed that it was possible to evaluate emotions to the target of agent with events related to liked or disliked objects as well as compute a certain situation of a target, which means that the proposed model can support contextual emotion appraisal. Secondly, the emotional transition model can  
Figure 10: The variation of emotion appraisal toward the events.