Awareness-Based Recommendation

In Artificial Intelligence and Robotics, one of the important issues is to design Human interface. There are two issues, one is the machine-centered interaction design to adapt humans for operating the robots or systems. Another one is the human-centered interaction design to make it adaptable for humans. This research aims at latter issue. This paper presents the interactive learning system to assist positive change in the preference of a human toward the true preference, then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the authors' system improves the efficiency for deciding the most preferred plan for both heavy users and light users.

Download Full-text

Awareness Based Recommendation

International Journal of Robotics Applications and Technologies ◽

10.4018/ijrat.2016010105 ◽

2016 ◽

Vol 4 (1) ◽

pp. 83-99

Author(s):

Tomohiro Yamaguchi ◽

Takuma Nishimura ◽

Keiki Takadama

Keyword(s):

Artificial Intelligence ◽

Interaction Design ◽

Interactive Learning ◽

Learning System ◽

Experimental Results ◽

Human Intelligence ◽

Human Interface ◽

True Preference ◽

Heavy Users ◽

And Robotics

In Artificial Intelligence and Robotics, one of the important issues is to design Human interface. There are two issues, one is the machine-centered interaction design to adapt humans for operating the robots or systems. Another one is the human-centered interaction design to make it adaptable for humans. This research aims at latter issue. This paper presents the interactive learning system to assist positive change in the preference of a human toward the true preference, then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the authors' system improves the efficiency for deciding the most preferred plan for both heavy users and light users.

Download Full-text

Awareness-Based Recommendation Toward a New Preference

Human Performance Technology ◽

10.4018/978-1-5225-8356-1.ch029 ◽

2019 ◽

pp. 572-593

Author(s):

Tomohiro Yamaguchi ◽

Takuma Nishimura ◽

Keiki Takadama

Keyword(s):

Interaction Design ◽

Design Research ◽

Learning System ◽

Human Intelligence ◽

Human Interface ◽

True Preference ◽

Heavy Users ◽

And Training ◽

And Robotics ◽

The Way

In mechatronics and robotics, one of the important issues is to design human interface. There are two issues on interaction design research. One is the way to education and training to adapt humans for operating the robots or interaction systems. Another one is the way to make interaction design adaptable for humans. This chapter research at the latter issue. This chapter describes the interactive learning system to assist positive change in the preference of a human toward the true preference; then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the system improves the efficiency for deciding the most preferred plan for both heavy users and light users.

Download Full-text

Awareness-Based Recommendation toward a New Preference

Advances in Computational Intelligence and Robotics - Handbook of Research on Advancements in Robotics and Mechatronics ◽

10.4018/978-1-4666-7387-8.ch009 ◽

2015 ◽

pp. 219-241

Author(s):

Tomohiro Yamaguchi ◽

Takuma Nishimura ◽

Keiki Takadama

Keyword(s):

Interaction Design ◽

Design Research ◽

Learning System ◽

Human Intelligence ◽

Human Interface ◽

True Preference ◽

Heavy Users ◽

And Training ◽

And Robotics ◽

The Way

In mechatronics and robotics, one of the important issues is to design human interface. There are two issues on interaction design research. One is the way to education and training to adapt humans for operating the robots or interaction systems. Another one is the way to make interaction design adaptable for humans. This chapter research at the latter issue. This chapter describes the interactive learning system to assist positive change in the preference of a human toward the true preference; then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the system improves the efficiency for deciding the most preferred plan for both heavy users and light users.

Download Full-text

Awareness-Based Recommendation by Passively Interactive Learning

Novel Design and Applications of Robotics Technologies - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-5225-5276-5.ch009 ◽

2018 ◽

pp. 247-275

Author(s):

Tomohiro Yamaguchi ◽

Takuma Nishimura ◽

Shota Nagahama ◽

Keiki Takadama

Keyword(s):

Interaction Design ◽

Interactive Learning ◽

Learning System ◽

Future Research ◽

Research Directions ◽

Human Interface ◽

True Preference ◽

Heavy Users ◽

Future Research Directions ◽

And Robotics

In artificial intelligence and robotics, one of the important issues is to design human interface. There are two issues: One is the machine-centered interaction design. Another one is the human-centered interaction design. This research aims at the latter issue. This chapter presents the interactive learning system to assist positive change in the preference of a human toward the true preference. Then evaluation of the awareness effect is discussed. The system behaves passively to reflect the human intelligence by visualizing the traces of his/her behaviors. Experimental results showed that subjects are divided into two groups, heavy users and light users, and that there are different effects between them under the same visualizing condition. They also showed that the authors' system improves the efficiency for deciding the most preferred plan for both heavy users and light users. As future research directions, a probabilistic event and its basic recommendation way are discussed.

Download Full-text

Learned Behavior

Integrating Cognitive Architectures into Virtual Character Design - Advances in Computational Intelligence and Robotics ◽

10.4018/978-1-5225-0454-2.ch004 ◽

2016 ◽

pp. 94-123 ◽

Cited By ~ 1

Author(s):

Jacquelyne Forgette ◽

Michael Katchabaw

Keyword(s):

Reinforcement Learning ◽

Virtual Environments ◽

Virtual Environment ◽

Virtual World ◽

Learning System ◽

Experimental Results ◽

Virtual Characters ◽

Learned Behavior ◽

The World ◽

Over Time

A key challenge in programming virtual environments is to produce virtual characters that are autonomous and capable of action selections that appear believable. In this chapter, motivations are used as a basis for learning using reinforcements. With motives driving the decisions of characters, their actions will appear less structured and repetitious, and more human in nature. This will also allow developers to easily create virtual characters with specific motivations, based mostly on their narrative purposes or roles in the virtual world. With minimum and maximum desirable motive values, the characters use reinforcement learning to drive action selection to maximize their rewards across all motives. Experimental results show that a character can learn to satisfy as many as four motives, even with significantly delayed rewards, and motive changes that are caused by other characters in the world. While the actions tested are simple in nature, they show the potential of a more complicated motivation driven reinforcement learning system. The developer need only define a character's motivations, and the character will learn to act realistically over time in the virtual environment.

Download Full-text

Relevé: An at-home ballet self-learning interactive system

KnE Engineering ◽

10.18502/keg.v2i2.622 ◽

2017 ◽

Vol 2 (2) ◽

pp. 242

Author(s):

Cenzi Wang ◽

Stephen Jia Wang

Keyword(s):

Interaction Design ◽

Learning System ◽

Interactive System ◽

Tangible Interaction ◽

Physical Computing ◽

Safety Issues ◽

Home Based ◽

Self Learning ◽

Ballet Dancing ◽

At Home

<p>Benefits from the recent technology advancement, such as physical computing and social media, it has become a global industry trend to provide intelligent exercise and self-learning support in an ‘at-home’ environment. However, it is still a design challenge to ensure the safety of users while enhancing their experiences when developing specific ‘at-home’ self-training programs which require high-level techniques, such as ballet dancing. This paper introduces Relevé - an interactive self-learning system for ballet with emphasis on various safety issues. Based on the professional knowledge of ballet dancing posture and kinematic movement research, Relevé intends to answer the needs of ballet dancing home-based self-teaching activities through online courses. The design has been based mainly on the methodologies of tangible interaction design. </p>

Download Full-text

The use of the Freeze-Framer Interactive Learning System in mental training

PsycEXTRA Dataset ◽

10.1037/e548052012-549 ◽

2007 ◽

Author(s):

Frank van den Berg ◽

Hardy Menkehorst

Keyword(s):

Interactive Learning ◽

Learning System ◽

Mental Training

Download Full-text

A UWB-Driven Self-Actuated Projector Platform for Interactive Augmented Reality Applications

Applied Sciences ◽

10.3390/app11062871 ◽

2021 ◽

Vol 11 (6) ◽

pp. 2871

Author(s):

Ahmed Elsharkawy ◽

Khawar Naheem ◽

Dongwoo Koo ◽

Mun Sang Kim

Keyword(s):

Augmented Reality ◽

Interaction Design ◽

Rapid Development ◽

Interactive Technology ◽

Ultra Wideband ◽

Wireless Sensor ◽

Interactive System ◽

Input Device ◽

Reasonable Accuracy ◽

Calibration Algorithm

With the rapid development of interactive technology, creating systems that allow users to define their interactive envelope freely and provide multi-interactive modalities is important to build up an intuitive interactive space. We present an indoor interactive system where a human can customize and interact through a projected screen utilizing the surrounding surfaces. An ultra-wideband (UWB) wireless sensor network was used to assist human-centered interaction design and navigate the self-actuated projector platform. We developed a UWB-based calibration algorithm to facilitate the interaction with the customized projected screens, where a hand-held input device was designed to perform mid-air interactive functions. Sixteen participants were recruited to evaluate the system performance. A prototype level implementation was tested inside a simulated museum environment, where a self-actuated projector provides interactive explanatory content for the on-display artifacts under the user’s command. Our results depict the applicability to designate the interactive screen efficiently indoors and interact with the augmented content with reasonable accuracy and relatively low workload. Our findings also provide valuable user experience information regarding the design of mobile and projection-based augmented reality systems, with the ability to overcome the limitations of other conventional techniques.

Download Full-text