1. A method for programming a computer to simulate human will-expression in response to an external direction input, comprising: comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure; preparing, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input; and outputting, by the computer, the mood factor.

2. The method of claim 1, wherein the direction input is a direction and wherein the hedonic interest relationship table is a hedonic emotional relationship table.

3. The method of claim 1, wherein the step of comparing the direction input with the hedonic interest relationship table comprises: obtaining the hedonic interest relationship table from an hedonic interest relationship resource; training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table; and, modelling the human emotions from at least some of the set of the human emotions.

4. The method according to claim 1, wherein the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms.

5. A method as claimed in claim 1, wherein the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure is conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.

6. A system for programming a computer to simulate human will-expression in response to an external direction input comprising: compare the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure; prepare, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input; and output, by the computer, the mood factor.

7. The system of claim 6, wherein the direction input is a direction direction and wherein the hedonic interest relationship table is a hedonic emotional relationship table.

8. The system of claim 6, wherein the step of comparing the direction input with the hedonic interest relationship table comprises: obtaining the hedonic interest relationship table from an hedonic interest relationship resource training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table; and , modelling the human emotions from at least some of the set of the human emotions.

9. The system of claim 6, wherein the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms.

10. The system of claim 6, wherein the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure is conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.   AI BASED WILLINGNESS EXPRESSION MODELLING TOOL FOR PSYCHOLOGICAL EVALUATION Abstract Method discloses simulation of human will-expression in response to an external direction input, such as by comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure. In certain implementations, the computer is responsible for constructing a range of emotional states based on human emotion models and then triggering transitions between those states in response to the user's directional input. Mood might be output by the computer as part of an embodiment. Fig. XX , C , Claims:Claims :

1. A method for programming a computer to simulate human will-expression in response to an external direction input, comprising: comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure; preparing, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input; and outputting, by the computer, the mood factor.

2. The method of claim 1, wherein the direction input is a direction and wherein the hedonic interest relationship table is a hedonic emotional relationship table.

3. The method of claim 1, wherein the step of comparing the direction input with the hedonic interest relationship table comprises: obtaining the hedonic interest relationship table from an hedonic interest relationship resource; training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table; and, modelling the human emotions from at least some of the set of the human emotions.

4. The method according to claim 1, wherein the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms.

5. A method as claimed in claim 1, wherein the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure is conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.

6. A system for programming a computer to simulate human will-expression in response to an external direction input comprising: compare the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure; prepare, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input; and output, by the computer, the mood factor.

7. The system of claim 6, wherein the direction input is a direction direction and wherein the hedonic interest relationship table is a hedonic emotional relationship table.

8. The system of claim 6, wherein the step of comparing the direction input with the hedonic interest relationship table comprises: obtaining the hedonic interest relationship table from an hedonic interest relationship resource training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table; and , modelling the human emotions from at least some of the set of the human emotions.

9. The system of claim 6, wherein the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms.

10. The system of claim 6, wherein the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure is conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.

Description:AI BASED WILLINGNESS EXPRESSION MODELLING TOOL FOR PSYCHOLOGICAL EVALUATION

Field of the Invention
[0001] The present invention relates generally to will-expression modelling device, more particularly to a system and method to simulate a human will-expression.

Background
[0002] The background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[0003] The willingness expression modelling tool (WEMT) is a psychological assessment tool that measures a person's willingness to engage in a particular behaviour or activity. The WEMT is based on the theory of planned behaviour, which proposes that attitudes, subjective norms, and perceived behavioural control all influence a person's intention to engage in a behaviour, which in turn influences their actual behaviour. The hedonic interest relationship table, also known as the pleasure-interest framework, is a psychological construct that describes the relationship between a person's level of interest and their level of pleasure or enjoyment in an activity and thus, psychological status. The framework is based on the idea that people engage in activities because they find them both interesting and enjoyable.
[0004] Research on the hedonic interest relationship table has focused on several key areas. One area of research has examined the impact of individual differences on the relationship between interest and psychology of status. Studies have found that people who are more curious and open-minded tend to experience more pleasure from activities that they find interesting, while those who are more risk-averse may experience less pleasure from novel or challenging activities. Studies have found that when people are interested in an activity, they are more motivated to engage in that activity and are more likely to persist in the face of challenges or obstacles. Furthermore, when people experience pleasure from an activity, they are more likely to engage in that activity again in the future.
[0005] Various technological solutions are disclosed in patent literature. Few of the exemplary documents are discussed below.
[0006] CN100375118C (By: AGI) provides idea expression model device of the present invention includes a spontaneous feeling unit, a knowledge database, and a conception unit. The spontaneous feeling section prepares feeling states in which human feelings are modeled as data in advance, and repeats state transition between these feeling states in accordance with a random model of schrodinger equation. In the knowledge database, knowledge data collected from the outside and correlation strength with emotional states are associated and stored in a classified manner, thereby simulating an idea expression source of a person affected by sensibility. And a conception unit for, when an external input is given, combining the external input with the emotional state of the spontaneous emotion unit, and searching for knowledge data from the knowledge database using the combination as a search key to simulate the human conception behaviour.
[0007] US9037526B2 (By: KOREA INSTITUTE OF INDUSTRIAL TECHNOLOGY) relates to apparatus for selecting a motion signifying artificial feeling is provided. The apparatus includes: an feeling expression setting unit configured to set probabilities of each feeling expression behaviour performed for each expression element of a robot for each predetermined feeling; a behaviour combination generation unit configured to generate at least one behaviour combination combined by randomly extracting the feeling expression behaviours in each expression element one by one; and a behaviour combination selection unit configured to calculate an average for the probabilities of the feeling expression behaviours included in each behaviour combination for each feeling of a robot and select behaviour combinations in which the average of the probabilities of the feeling expression behaviours most approximates the predetermined feeling value of a robot from each behaviour combination.
[0008] JP7199451B2 (By: INSTITUTE OF SOFTWARE - CHINESE ACADEMY OF SCIENCES) discloses a sensitive interaction device. The sensitive interaction device includes a sensitive interaction calculation module, which includes a user intent calculation unit. The user intent calculating unit receives emotional related data and an emotional state of the user and recognizes the user intent based on the emotional related data and the emotional state. The user intent comprises emotional intent and/or interaction intent, the emotional intent corresponds to and includes emotional needs of the emotional state, and the interaction intent comprises one or more transactional intents.
[0009] However, the technological solutions to simulate human will-expression suffers from various limitations such as, complexity, etc. As a result, a technique, system, and software are required for developing AI based willingness expression modelling tool for psychological evaluation.
[00010] All references, including publications, patent applications, and patents, cited herein are hereby incorporated by reference to the same extent as if each reference were individually and specifically indicated to be incorporated by reference and were set forth in its entirety herein.

Summary
[00011] The present invention relates generally to will-expression modelling device, more particularly to a system and method to simulate a human will-expression.
[00012] This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Furthermore, the claimed subject matter is not limited to implementations that solve any or all disadvantages noted in any part of this disclosure.
[00013] The following paragraphs provide additional support for the claims of the subject application.
[00014] Embodiments of the present disclosure may include a method for programming a computer to simulate human will-expression in response to an external direction input, including comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure. Embodiments may also include preparing, plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input. Embodiments may also include outputting, by the computer, the mood factor.
[00015] In some embodiments, the hedonic interest relationship table may be a hedonic emotional relationship table. In some embodiments, the step of comparing the direction input with the hedonic interest relationship table may include obtaining the hedonic interest relationship table from an hedonic interest relationship resource. Embodiments may also include training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table. Embodiments may also include modelling the human emotions from at least some of the set of the human emotions.
[00016] In some embodiments, the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms. In some embodiments, the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure may be conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.
[00017] Embodiments of the present disclosure may also include a system for programming a computer to simulate human will-expression in response to an external direction input including compare the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure. Embodiments may also include prepare, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input. Embodiments may also include output, by the computer, the mood factor.
[00018] In some embodiments, the hedonic interest relationship table may be a hedonic emotional relationship table. In some embodiments, the step of comparing the direction input with the hedonic interest relationship table may include obtaining the hedonic interest relationship table from an hedonic interest relationship resource. Embodiments may also include training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table. Embodiments may also include, modelling the human emotions from at least some of the set of the human emotions.
[00019] In some embodiments, the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms. In some embodiments, the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure may be conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.

 
Brief Description of the Drawings
[00020] Embodiments will now be described in more detail in relation to the enclosed drawings, in which:
[00021] FIG. 1 is a flowchart illustrating a method for AI based willingness expression modelling tool for psychological evaluation, according to some embodiments of the present disclosure.
[00022] FIG. 2 is a flowchart further illustrating the detailed method of FIG. 1, according to some embodiments of the present disclosure.
[00023] FIG. 3 is a block diagram illustrating a system for AI based willingness expression modelling tool for psychological evaluation, according to some embodiments of the present disclosure.
[00024] FIG. 4 is a block diagram further illustrating the extended system of FIG. 3, according to some embodiments of the present disclosure.
Detailed Description
[00025] The following is a detailed description of exemplary embodiments to illustrate the principles of the invention. The embodiments are provided to illustrate aspects of the invention, but the invention is not limited to any embodiment. The scope of the invention encompasses numerous alternatives, modifications and equivalent; it is limited only by the claims.
[00026] Numerous specific details are set forth in the following description in order to provide a thorough understanding of the invention. However, the invention may be practiced according to the claims without some or all of these specific details. For the purpose of clarity, technical material that is known in the technical fields related to the invention has not been described in detail so that the invention is not unnecessarily obscured.
[00027] The present invention relates generally to will-expression modelling device, more particularly to a system and method to simulate a human will-expression.
[00028] FIG. 1 is a flowchart illustrating a method for AI based willingness expression modelling tool for psychological evaluation, according to some embodiments of the present disclosure. In some embodiments, at 110, the method may include comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure. At 120, the method may include preparing, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input. At 130, the method may include outputting, by the computer, the mood factor.
[00029] The hedonic interest relationship table may be a hedonic emotional relationship table. In some embodiments, the step of preparing the number of emotional states may include preparing an intention-based model of the human emotion by machine learning mechanisms. In some embodiments, the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure may be conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.
[00030] FIG. 2 is a flowchart further illustrating the detailed method of FIG. 1, according to some embodiments of the present disclosure. In some embodiments, the step of comparing the direction input with the hedonic interest relationship table comprises, the method may include 210 to 230.
[00031] FIG. 3 is a block diagram illustrating a system for AI based willingness expression modelling tool for psychological evaluation, according to some embodiments of the present disclosure. In some embodiments, the system 300 may also include output 310, by the computer, the mood factor. Compare the direction input with a predetermined hedonic interest relationship table. The result be a mood factor representing pleasure or displeasure. Prepare, by the computer, a plurality of emotional states obtained by modelling human emotions. The computer trigger state transitions in the emotional states as a result of the direction input.
[00032] In some embodiments, the step includes obtaining the hedonic interest relationship table from an hedonic interest relationship resource. Training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table, modelling the human emotions from at least some of the set of the human emotions. In some embodiments, the step of preparing the number of emotional states. Preparing an intention-based model of the human emotion by machine learning mechanisms.
[00033] FIG. 4 is a block diagram further illustrating the extended system 300 of FIG. 3, according to some embodiments of the present disclosure. In some embodiments, the step of. The computer compare the direction input with a predetermined hedonic interest relationship table. The result be a mood factor representing pleasure or displeasure may be conducted by at least one of one of one or more human emotions or one of a group.
[00034] Methods for programming a computer to mimic human will expression in response to an external direction input are within the scope of the present disclosure. These methods may involve comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure. In certain implementations, the computer is responsible for constructing a range of emotional states based on human emotion models and then triggering transitions between those states in response to the user's directional input. Mood might be output by the computer as part of an embodiment.
[00035] As an example of a direction input, we may consider several implementations. The hedonic interest connection table may also be a hedonic emotion relationship table in some implementations. Hedonic interest relationship tables may be obtained from a hedonic interest relationship resource in certain implementations, and then compared to the direction input. One other method for realising embodiments is to use the hedonic interest connection table to train a model of a subset of human emotions. Certain embodiments may also include emotional modelling, based on at least some human feelings.
[00036] In certain implementations, an intention-based model of human emotion is constructed using machine learning processes as part of the stage of preparing the number of emotional states. The step of comparing the direction input to a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure can be performed by at least one human emotion or one of a group consisting of anger, attraction, sadness, excitement, and boredom.
[00037] The present disclosure can also be understood as a system for teaching a computer to mimic human will-expression in response to an external direction input, such as by comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure. It is also possible for embodiments to include the preparation by the computer of a set of emotional states derived from the modelling of human emotions, and the triggering of state transitions in the emotional states by the computer in response to the direction input. Mood information may be generated on the computer and used in embodiments.
[00038] The direction input might be a direction in certain implementations. The hedonic interest relationship table may also be a hedonic emotional connection table in certain implementations. Hedonic interest relationship tables may be obtained from a hedonic interest relationship resource in certain implementations, and then compared to the direction input. One other method for realising embodiments is to use the hedonic interest connection table to train a model of a subset of human emotions. The modelling of human emotions from at least a subset of the whole human emotion repertoire is also possible in embodiments.
[00039] In certain implementations, an intention-based model of human emotion is constructed using machine learning processes as part of the stage of preparing the number of emotional states. Anger, attraction, sadness, anger, and excitement are all examples of human emotions that could be used in place of the computer in the step where the direction input is compared to a predetermined hedonic interest relationship table and the result is a mood factor representing pleasure or displeasure.
[00040] A number of implementations have been described. Nevertheless, various modifications may be made without departing from the spirit and scope of the invention. In addition, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. In addition, other steps may be provided, or steps may be eliminated, from the described flows, and other components may be added to, or removed from, the described systems. Accordingly, other implementations are within the scope of the following claims.
[00041] Various techniques may be described herein in the general context of software, hardware elements, or program modules. Generally, such modules include routines, programs, objects, elements, components, data structures, and so forth that perform particular tasks or implement particular abstract data types. The terms module, functionality, and component as used herein generally represent software, firmware, hardware, or a combination thereof. The features of the techniques described herein are platform-independent, meaning that the techniques may be implemented on a variety of commercial computing platforms having a variety of processors Executable instructions stored on the computer-readable media or memory can include, for example, an operating system, a data management framework , and/or other modules, programs, or applications that are loadable and executable by the processor(s) or any appropriate hardware logic components/CPU(s).
[00042] It will be obvious to a person skilled in the art that, as the technology advances, the inventive concept can be implemented in various ways. The above described embodiments are given for describing rather than limiting the disclosure, and it is to be understood that modifications and variations may be resorted to without departing from the spirit and scope of the disclosure as those skilled in the art readily understand. Such modifications and variations are considered to be within the scope of the disclosure and the appended claims. The protection scope of the disclosure is defined by the accompanying claims.
[00043] Conditional language such as, among others, include, including, comprise, comprising, can, could, might or may, unless specifically stated otherwise, is understood within the context to present that certain examples include, while other examples do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that certain features, elements and/or steps are in any way required for one or more examples or that one or more examples necessarily include logic for deciding, with or without user input or prompting, whether certain features, elements and/or steps are included or are to be performed in any particular example. Conjunctive language such as the phrase at least one of X, Y or Z, unless specifically stated otherwise, is to be understood to present that an item, term, etc. may be any of X, Y, or Z, or a combination or sub-combination thereof.As described above, the exemplary embodiment provides both a method and corresponding apparatus consisting of various modules providing functionality for performing the steps of the method. The modules/engines may be implemented as hardware (embodied in one or more chips including an integrated circuit such as an application specific integrated circuit), or may be implemented as software or firmware for execution by a computer processor. In particular, in the case of firmware or software, the exemplary embodiment can be provided as a computer program product including a computer readable storage structure embodying computer program code (i.e., software or firmware) thereon for execution by the computer processor.
[00044] Modifications, additions, or omissions may be made to the systems and apparatuses described herein without departing from the scope of the disclosure. The components of the systems and apparatuses may be integrated or separated. Moreover, the operations of the systems and apparatuses may be performed by more, fewer, or other components. Additionally, operations of the systems and apparatuses may be performed using any suitable logic comprising software, hardware, and/or other logic. As used in this document, each refers to each member of a set or each member of a subset of a set.
[00045] Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and sub-combination of these embodiments. Accordingly, all embodiments may be combined in any way and/or combination, and the present specification, including the drawings, shall be construed to constitute a complete written description of all combinations and sub-combinations of the embodiments described herein, and of the manner and process of making and using them, and shall support claims to any such combination or sub-combination.
[00046] The above description is intended to be illustrative, and not restrictive. Although the present disclosure has been described with references to specific illustrative examples and implementations, it will be recognized that the present disclosure is not limited to the examples and implementations described. The scope of the disclosure should be determined with reference to the following claims, along with the full scope of equivalents to which the claims are entitled.

 

Claims
I/We Claim:
1. A method for programming a computer to simulate human will-expression in response to an external direction input, comprising: comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure; preparing, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input; and outputting, by the computer, the mood factor.

2. The method of claim 1, wherein the direction input is a direction and wherein the hedonic interest relationship table is a hedonic emotional relationship table.

3. The method of claim 1, wherein the step of comparing the direction input with the hedonic interest relationship table comprises: obtaining the hedonic interest relationship table from an hedonic interest relationship resource; training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table; and, modelling the human emotions from at least some of the set of the human emotions.

4. The method according to claim 1, wherein the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms.

5. A method as claimed in claim 1, wherein the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure is conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.

6. A system for programming a computer to simulate human will-expression in response to an external direction input comprising:
compare the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure;
prepare, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input; and
output, by the computer, the mood factor.

7. The system of claim 6, wherein the direction input is a direction direction and wherein the hedonic interest relationship table is a hedonic emotional relationship table.

8. The system of claim 6, wherein the step of comparing the direction input with the hedonic interest relationship table comprises:
obtaining the hedonic interest relationship table from an hedonic interest relationship resource
training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table; and
, modelling the human emotions from at least some of the set of the human emotions.

9. The system of claim 6, wherein the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms.

10. The system of claim 6, wherein the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure is conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.

 

AI BASED WILLINGNESS EXPRESSION MODELLING TOOL FOR PSYCHOLOGICAL EVALUATION

Abstract
Method discloses simulation of human will-expression in response to an external direction input, such as by comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure. In certain implementations, the computer is responsible for constructing a range of emotional states based on human emotion models and then triggering transitions between those states in response to the user's directional input. Mood might be output by the computer as part of an embodiment.

Fig. XX , C , Claims:Claims
I/We Claim:
1. A method for programming a computer to simulate human will-expression in response to an external direction input, comprising: comparing the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure; preparing, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input; and outputting, by the computer, the mood factor.

2. The method of claim 1, wherein the direction input is a direction and wherein the hedonic interest relationship table is a hedonic emotional relationship table.

3. The method of claim 1, wherein the step of comparing the direction input with the hedonic interest relationship table comprises: obtaining the hedonic interest relationship table from an hedonic interest relationship resource; training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table; and, modelling the human emotions from at least some of the set of the human emotions.

4. The method according to claim 1, wherein the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms.

5. A method as claimed in claim 1, wherein the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure is conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.

6. A system for programming a computer to simulate human will-expression in response to an external direction input comprising:
compare the direction input with a predetermined hedonic interest relationship table and having the result be a mood factor representing pleasure or displeasure;
prepare, by the computer, a plurality of emotional states obtained by modelling human emotions and having the computer trigger state transitions in the emotional states as a result of the direction input; and
output, by the computer, the mood factor.

7. The system of claim 6, wherein the direction input is a direction direction and wherein the hedonic interest relationship table is a hedonic emotional relationship table.

8. The system of claim 6, wherein the step of comparing the direction input with the hedonic interest relationship table comprises:
obtaining the hedonic interest relationship table from an hedonic interest relationship resource
training a model, by machine learning, of a specific set of the human emotions using the hedonic interest relationship table; and
, modelling the human emotions from at least some of the set of the human emotions.

9. The system of claim 6, wherein the step of preparing the number of emotional states includes preparing an intention-based model of the human emotion by machine learning mechanisms.

10. The system of claim 6, wherein the step of having the computer compare the direction input with a predetermined hedonic interest relationship table and have the result be a mood factor representing pleasure or displeasure is conducted by at least one of one of one or more human emotions or one of a group consisting of anger, attraction, sadness, anger and excitement.