Emotion-oriented agent in mental state transition learning network

Ichimura, Tsuyoshi; Mera, Kazuya

doi:10.1504/ijcistudies.2013.054773

Cited by 6 publications

(6 citation statements)

References 16 publications

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“…1) F V is unknown: The token in P ji is the agreement value as the antecedent part in Type1 in Fig.7(a) and then, the minimum value among them is calculated by Eq. (7). If the place which takes the minimum value have an unknown F V , the agreement value is 0.5.…”

Section: B Improvement Of Learning Methodsmentioning

confidence: 98%

“…7(a) and then, the minimum value among them is calculated by Eq. (7). If the place which takes the minimum value have an unknown F V , the agreement value is 0.5.…”

Section: B Improvement Of Learning Methodsmentioning

confidence: 98%

“…The assumption of discrete emotion state is that human emotion is classified into some kinds of stable discrete states, called "mental state," and the variance of emotions occurs in the transition from a state to other state with an arbitrary probability. Mera and Ichimura [6], [7] developed a computer agent that can transit a mental state in MSTN based on analysis of emotion by EGC method. EGC calculates emotion and the type of the aroused emotion is used to transit mental state [6].…”

Section: Introductionmentioning

confidence: 99%

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An estimation of favorite value in emotion generating calculation by Fuzzy Petri Net

Ichimura

Tanabe

2013

2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)

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Emotion Generating Calculations (EGC) method based on the Emotion Eliciting Condition Theory can decide whether an event arouses pleasure or not and quantify the degree under the event. An event in the form of Case Frame representation is classified into 12 types of calculations. However, the weak point in EGC is Favorite Value (F V ) as the personal taste information. In order to improve the problem, this paper challenges to establish a learning method to learn speaker's taste information from dialog. Especially, the learning method employs Fuzzy Petri Net to find an appropriate F V to a word which has the unknown F V . This paper discusses the effective learning method to improve a weak point of EGC when a missing value of F V exists.

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Section: B Improvement Of Learning Methodsmentioning

confidence: 98%

“…7(a) and then, the minimum value among them is calculated by Eq. (7). If the place which takes the minimum value have an unknown F V , the agreement value is 0.5.…”

Section: B Improvement Of Learning Methodsmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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An estimation of favorite value in emotion generating calculation by Fuzzy Petri Net

Ichimura

Tanabe

2013

2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)

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“…The assumption of discrete emotion state is that human emotion is classified into some kinds of stable discrete states, called "mental state," and the variance of emotions occurs in the transition from a state to the other state with an arbitrary probability. Mera and Ichimura [6], [7] developed a computer agent that can transit a mental state in MSTN to the other state according to the kinds of emotion generated by EGC. The strength of emotion and the type of the aroused emotion by EGC arouses the transition of mental states [6].…”

Section: Introductionmentioning

confidence: 99%

Affective recommendation system for tourists by using Emotion Generating Calculations

Ichimura¹,

Tachibana

2014

2014 IEEE 7th International Workshop on Computational Intelligence and Applications (IWCIA)

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An emotion orientated intelligent interface consists of Emotion Generating Calculations (EGC) and Mental State Transition Network (MSTN). We have developed the Android EGC application software which the agent works to evaluate the feelings in the conversation. In this paper, we develop the tourist information system which can estimate the user's feelings at the sightseeing spot. The system can recommend the sightseeing spot and the local food corresponded to the user's feeling. The system calculates the recommendation list by the estimate function which consists of Google search results, the important degree of a term at the sightseeing website, and the the aroused emotion by EGC. In order to show the effectiveness, this paper describes the experimental results for some situations during Hiroshima sightseeing.

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“…Our research group proposed a method to calculate the agent's emotion from the contents of utterances and to express emotions which are aroused in computer agent [1], [2], [3]. Emotion Generating Calculations (EGC) method [1] based on the Emotion Eliciting Condition Theory [5] can decide whether an event arouses pleasure or not and quantify the degree under the event.…”

Section: Introductionmentioning

confidence: 99%

An adaptive learning method of personality trait based mood in Mental State Transition Network by recurrent neural network

Ichimura¹,

Tanabe²,

Yamashita

2014

2014 IEEE 7th International Workshop on Computational Intelligence and Applications (IWCIA)

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Mental State Transition Network (MSTN) is a basic concept of approximating to human psychological and mental responses. A stimulus calculated by Emotion Generating Calculations (EGC) method can cause the transition of mood from an emotional state to others. In this paper, the agent can interact with human to realize smooth communication by an adaptive learning method of the user's personality trait based mood. The learning method consists of the profit sharing (PS) method and the recurrent neural network (RNN). An emotion for sensor inputs to MSTN is calculated by EGC and the variance of emotion leads to the change of mental state, and then the sequence of states forms an episode. In order to learn the tendency of personality trait effectively, the ineffective rules should be removed from the episode. PS method finds out a detour in episode and should be deleted. Furthermore, RNN works to realize the variance of user's mood. Some experimental results were shown the success of representing a various human's delicate emotion.

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Emotion-oriented agent in mental state transition learning network

Cited by 6 publications

References 16 publications

An estimation of favorite value in emotion generating calculation by Fuzzy Petri Net

An estimation of favorite value in emotion generating calculation by Fuzzy Petri Net

Affective recommendation system for tourists by using Emotion Generating Calculations

An adaptive learning method of personality trait based mood in Mental State Transition Network by recurrent neural network

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