A project to compose a modular AI certification system in university education and its inherent chance to verify, validate, and refine AI teaching by AI technologies. - LibraryPressUF. - 1 Online-Ressource (6 Seiten)Online-Ausg.: Proceedings of the FLAIRS-36, May 14-17, 2023, Clearwater Beach, Florida, USA / published by the LibraryPressUF
A current project of the German Federal State of Thuringia aims at bundling the various AI teaching activities of the involved universities that includes besides technological also social issues. On their way to meet the project objectives, the authors aim at utilizing such unique opportunity to consider the various successful experiences in teaching several AI content issues of the project members to revisit a formerly developed concept of semi-formally representing didactic knowledge and making it a subject of Knowledge Engineering technologies such as consistency issues as well as chances to validate learning paths and refine them based on the validation results. Ideas towards this objective and first results are sketched in this paper.
The evolution of the fAIble system to automatically compose and narrate stories for children. - In: Journal of experimental & theoretical artificial intelligence, ISSN 1362-3079, Bd. 0 (2022), 0, S. 1-46
This article describes our long-term research into automated story generation and our resulting story generation architecture called fAIble that incorporates several innovations. fAIble determines each event that occurs in the tale using a combination of scripted sequences and stochastically chosen events. The probability of an event occurring is based on the skills and personalities of the characters who have agency. Event selection is also influenced by the context of the situation faced by the characters. Each event is associated with a description in grammatically-correct natural language that can be narrated orally via text-to-speech. We describe the evolution of fAIble, its architecture and the results of our independent evaluation of each of the four progressively developed fAIble prototypes (fAIble 0, I, II and III), as tested with human test subjects. On a continuous scale where 0 means unacceptable, 1 means acceptable and 2 means optimal, the composite human test subject rating average from the independent tests of the prototypes was 0.933. The paper also describes a summative assessment where test subjects were asked to review stories from all four prototypes and rank them comparatively. These comparative results indicate an improvement from the original (fAIble 0) to the last one (fAIble III).
Character depth and sentence diversification in automated narrative generation. - In: Proceedings of the Thirty-third International Florida Artificial Intelligence Research Society Conference, (2020), S. 21-26
This paper describes and discusses methods for improving character depth and sentence diversification in automated storytelling systems. The fAIble III system that is the subject of this paper addresses a major limitation of its immediate predecessor (fAIble II) in that the characters in its stories seemed to act in a vacuum, without any apparent reasons for their choices or emotions. This is accomplished through generating character backstories. fAIble III also addresses the diversity of generated sentences with a pattern recognition system that removes many of the awkward and repetitive sentences that drew negative comments in the testing of fAIble I and II. Lastly, stories generated by fAIble II and fAIble III are compared and empirical test results are presented.
Embodiment matters: toward culture-specific robotized counselling. - In: Journal of reliable intelligent environments, ISSN 2199-4676, Bd. 6 (2020), 3, S. 129-139
In this paper, we propose adding the traditional Japanese nodding behavior to the repertoire of social movements to be used in the context of human-robot interaction. Our approach is motivated by the notion that in many cultures, trust-building can be boosted by small body gestures. We discuss the integration of a robot capable of such movements within CRECA, our context-respectful counseling agent. The frequent nodding called "unazuki" in Japan, often accompanying the "un-un" sound (meaning "I agree") of Japanese onomatopoeia, underlines empathy and embodies unconditioned approval. We argue that unazuki creates more empathy and promotes longer conversation between the robotic counsellor and people. We set up an experiment involving ten subjects to verify these effects. Our quantitative evaluation is based on the classic metrics of utterance, adapted to support the Japanese language. Interactions featuring "unazuki" showed higher value of this metrics. Moreover, subjects assessed the counselling robot's trustworthiness and kindness as "very high" (Likert scale: 5.5 versus 3-4.5) showing the effect of social gestures in promoting empathetic dialogue to general people including the younger generation. Our findings support the importance of social movements when using robotized agents as a therapeutic tool aimed at improving emotional state and social interactions, with unambiguous evidence that embodiment can have a positive impact that warrants further exploration. The 3D printable design of our robot supports creating culture-specific libraries of social movements, adapting the gestural repertoire to different human cultures.
Context-assisted test cases reduction for cloud validation. - In: SSRN eLibrary, ISSN 1556-5068, (2020), insges. 14 S.
Last revised: 4 May 2020
Cloud computing is currently receiving much attention from the industry, government, and academia. It has changed the way computation is performed and how services are delivered to customers. Most importantly, cloud services change the way we design software, handle data, and perform testing. In cloud computing, testing is delivered as a service (TaaS). Case testing is one of the most common validation approaches for software. However, executing test cases on a software system could be expensive and time consuming. Therefore, test case reduction is performed to minimize the number of test cases to be executed on the system. In this paper, we introduce a validation method called Context-Assisted Test Case Reduction (CATCR) for systems that are deployed on the cloud. In CATCR, test cases are reduced based on the context of the validation process. The results of previous test cases are used to select the next set of test cases while the validation process is ongoing. The minimized set of test cases needs to have effective coverage of the entire system. To evaluate CATCR, an experimental evaluation is performed through Amazon's Cloud and a Java validation tool. Experimental results are recorded and presented.
High performance personal adaptation speech recognition framework by incremental learning with plural language models. - In: The 15th International Conference on Signal Image Technology & Internet Based Systems, (2019), S. 470-474
Robotized counselor evaluation using linguistic detection of feeling polarity change. - In: 2019 IEEE Symposium Series on Computational Intelligence, (2019), S. 962-967
In Japan, many people suffer from bad conditions of their mental health with an increasing tendency that should be alarmed. For this reason, a counseling robot was created in our former work and enhanced more and more. Our former quantitative evaluation based on the utterance amount. Here, we provide a new solution on evaluating this system. We introduce an evaluation polarity of the utterance contents by using a polarity dictionary This evaluates the feeling polarity of utterances by positive through negative degree on a scale from -1 (negative) to +1 (positive). Combined with generally used conventional impression evaluation by a questionnaire, it provides a much better way to evaluate the performance of our Counseling Agent Robot.
Maintaining diversity in an SVM integrated case based GA for solar flare prediction. - In: 2019 IEEE Symposium Series on Computational Intelligence, (2019), S. 353-360
Unusual intense solar flares may cause serious calamities such as those damaging electric/nuclear power plants. It is thereupon highly demanded, but is quite difficult to predict intense solar flares due to the imbalanced character of the available data. To cope with this problem, we have herefore developed and applied a Case Based Genetic Algorithm (CBGALO) that contains a local optimizer, which is a Support Vector Machine (SVM). However, the prediction performance significantly depends on input data for learning. Hereupon, CBGALO is further extended by a Case Based automatically restartable Good combination searching GA for both learning features and input data (CBRsGcmbGA). Even the powerful but computationally expensive Deep Learning cannot automatically (evolutionarily, in our approach) search the learning data. Our approach solved this problem a little better by the case-based approach. However, it became obvious that even this work suffers from the typical GA effect in falling into local optima. To improve the results, we newly developed hence a diversity maintenance approach that inserts good individuals with large Hamming distance into the case base as elite individuals in GAs population. In 2 out of 3 classes of solar flares, the performance of our new approach became as high as the best ones among the conventional world top records. Namely, even in ≥ C class solar flares, our approach applying the Hamming distance to increase diversity had as high a performance 0.662 as compared with the conventional world top record 0.650.
More general evaluation of a client-centered counseling agent. - In: 2019 IEEE World Congress on Services, (2019), S. 190-196
A lot of people in Japan suffer from bad conditions of their mental health with an increasing tendency, in particular jobseekers and elderly persons. The classical way to solve their problem is to consult a counselor, who treats these people in a way to become aware of the core of their problem and to solve it. However, the number of well qualified counselors is limited. For this purpose, we developed a VCA (Virtual Counseling Agent) as a further evolution of a formerly developed CRECA (Context Respectful Counseling Agent). CRECA. CRECA had a text interface. To much more imitate a human counselor, VCA has an image avatar and a voice conversation using the Google Cloud audio API. Further, VCA is made independent of counseling content fields. Thus, it is more generalized than CRECA or ELIZA in order for every people to easily use everywhere in every situation. Here, VCA, CRECA, and ELIZA are comparatively evaluated by questionnaire after the use of 10 college students having career problems as well as elderly persons struggling with modern IT. As a result, VCA significantly exceeded the average value of ELIZA along with the significant difference at the level of 5%. Moreover, average of the evaluation value is not worse than CRECA. Compared to CRECA, VCA does not limit the content and field of consultation. Especially, elderly persons struggling with modern IT could not use CRECA that have only text interface. It can be used generally at any time in everyday natural conversation. It can easily be used by elderly people and the digital divided due to voice conversion.
Visualization system for analyzing customer comments in marketing research support system. - In: 2019 IEEE World Congress on Services, (2019), S. 141-146
Since marketing research on theme parks such as Tokyo Disney Land is costly, we developed an efficient opinion collection system. However, it is difficult for the interviewer to extract characteristic opinions from several opinions. To cope with this problem, we classify emotions for opinions based on the wheel of Plutchik. We further propose a method of displaying them on a map for visualization. The evaluation result by questionnaires is 4.75 on average out of 5 scales. The result shows that the proposed system can support the action of proposing business ideas.