This paper describes the design concept and implementation of a software platform for realization of symbiotic robots that interact intelligently with human in symbiosis manner. Such robots require proper combination of various technologies on a common platform that allows them to work co-operatively. "SPAK" has been developed to serve this purpose. It is a Java-based software platform to support knowledge processing and co-ordination of tasks among several software modules and agents representing the robotic hardware connected on a network. SPAK features frame-based knowledge system, a GUI knowledge building tool, forward and backward chaining engines, networking support, and class libraries for building software agent components. Beside the robotic applications, SPAK can be used as a general-purpose frame system as well. An experimental application of SPAK in human-robot interaction is also given.

This paper presents the concepts and methodology of knowledge-based information modeling based on Cognitive Science for realizing the autonomous humanoid service robotic arm and hand system HARIS. The HARIS robotic system consists of model-based 3D vision, intelligent scheduler, computerized arm/hand controller, humanoid HARIS arm/hand unit and human interface, and aims to serve the aged and disabled on desk-top object manipulations. The world model, i.e., a shared knowledge base, is introduced to work as a communication channel among the software modules. The task scheduling as well as the 3D-vision is based on Cognitive Science, i.e., a human's way of vision and scheduling is considered in designing the knowledge-based software system. The key idea is to use "words" in describing a scene, scheduling tasks, controlling an arm and hand, and interacting with a human. The world model plays a key role in fusing a variety of distributed functions. The generalized frame-based knowledge engineering environment ZERO++ has been effectively used as a software platform in implementing the system. The experimental system is working within a limited situation successfully. Through the introduction of Cognitive Science-based information modeling we have learned useful hints for realizing human-robot symbiosis, that is our long term goal of the project.

The background concepts and methodologies of the knowledge-based program understander ALPUS is discussed. ALPUS understands user's buggy Pascal programs using four kinds of programming knowledge: the knowledge on algorithms, programming techniques, the Pascal language, and logical bugs. The knowledge on algorithms, the key knowledge, is represented in a form of hierarchical data structure called Hierarchical Procedure Graph (HPG). In HPG each node represents a chunk of operations called process," which is consisted of sub-processes. The other knowledge is maintained as independent knowledge bases and linked to associated processes of the HPG. The knowledge about bugs acquired by cognitive experiment is grouped into three categories: bugs on algorithms, programming techniques, and the Pascal language, and connected to associated elements of programming knowledge respectively. ALPUS tries to understand user's buggy programs, detects logical bugs, infers user's intentions, and gives advices for fixing bugs. Program understanding is achieved by three steps: normalization, variable identification, and process and technique identification. Normalization results in improving flexibility of understanding. Variable, process and technique identifications are achieved by knowledge-based pattern matching. Intentions are inferred by means of information attached to buggy patterns. The result of comprehension is reported to a user (i.e., student). Experimental results using Quicksort programs written by students show that the HPG formalism is quite powerful in understanding algorithm-oriented programs. The ALPUS's way of program comprehension is useful in the situation of programming education in an intermediate class of an engineering school. The ALPUS system is a subsystem of the intelligent programming environment INTELLITUTOR for learning programming, which was implemented in the frame-based knowledge engineering environment ZERO on a UNIX workstation.

In this paper, we propose a new online authoring tool for e-Learning system to meet the social demands for internationalized higher education. The tool includes two functions – an authoring function for creating video-based content by the instructor, and a viewing function for self-learning by students. In the authoring function, an instructor creates key markings onto the raw video stream to produce virtual video clips related to each slide. With key markings, some parts of the raw video stream can be easily skipped. The virtual video clips form an aggregated video stream that is used to synchronize with the slide presentation to create learning content. The synchronized content can be previewed immediately at the client computer prior to saving at the server. The aggregated video becomes the baseline for the viewing function. Based on aggregated video stream methodology, content editing requires only the changing of key markings without editing the raw video file. Furthermore, video and pointer synchronization is also proposed for enhancing the students' learning efficiency. In viewing function, video quality control and an adaptive video buffering method are implemented to support usage in various network environments. The total system is optimized to support cross-platform and cloud computing to break the limitation of various usages. The proposed method can provide simple authoring processes with clear user interface design for instructors, and help students utilize learning contents effectively and efficiently. In the user acceptance evaluation, most respondents agree with the usefulness, ease-of-use, and user satisfaction of the proposed system. The overall results show that the proposed authoring and viewing tools have higher user acceptance as a tool for e-Learning.

Knowledge-based program understanding is widely known as one of the key issues in programming education support systems and environments for novices. Most program understanders, however, have limitations. One of them is an ability to deal with a single programming language, while human tutors can comprehend plural languages by means of generalized knowledge on programming languages and techniques. This paper proposes the concepts and methodology of the knowledge-based program understander ALPUS II, which deals with plural programming languages, i. e. , Pascal and C, by means of generalized abstract syntax AL and knowledge representations based on it. ALPUS II is an extension of ALPUS, which dealt with a single programming language Pascal, and is a sub-system of an intelligent programming environment INTELLITUTOR. The INTELLITUTOR system consists of a guided programming editor GUIDE and a knowledge-based program understander ALPUS II, and is available on the Internet. In the process of comprehension source statements written in Pascal or C are translated into AL representation first. Since the contents of the programming knowledge bases are adjusted to deal with the AL representations the program comprehension procedure is available for both Pascal and C. It is possible to append other programming languages by simply attaching a transformation module for each additional procedural language. It is noted that knowledge acquisition tasks for additional languages are not needed since the contents of the knowledge base are generalized for multiple use. The INTELLITUTOR system was implemented in the frame-based knowledge engineering environment ZERO on a UNIX server machine in the Internet environment. ALPUS II demonstrates interesting features in program comprehension for the C language by means of the transformed knowledge from the already available knowledge for Pascal, which was developed for ALPUS, in a feasibility study. The current version of ALPUS II supports almost full specifications for Pascal and a Pascal-associated subset for C. This limitation should be reasonable for programming practice at freshmen classes of a university.

This paper discusses the experimental evaluation of the knowledge-based program understander ALPUS and methods of program normalization based on the evaluation to improve the flexibility of the system performance. ALPUS comprehends students' buggy Pascal programs using four kinds of programming knowledge, detects logical bugs, infers user's intentions and gives advice for fixing bugs. By means of the combination of the pattern matching technique and the HPG-based formalism of programming knowledge in addition to program normalization high performance of comprehension has been achieved for relatively complex programs such as Quicksort programs. The experimental evaluation told that program normalization would solve some 55% of unsucceeded student programs. Program normalization has contributed both in decreasing the number of knowledge patterns and increasing the flexibility. This paper proposes a five-step normalization procedure which works well in an experimental situation.

This paper describes the concepts and methodologies of the INTELLITUTOR system which is an integrated intelligent programming environment for learning programming. INTELLITUTOR attempts to work as a human programming tutor to guide a user, i.e., a student, in writing a computer program, to detect logical errors within it, and to make advices not only for fixing them but also for letting him notice his misunderstandings. The system consists of three major modules, i.e., GUIDE, ALPUS and TUTOR. GUIDE is a guided editor for easy coding, ALPUS is an algorithm-based program understander, and TUTOR is an embedded-intelligent tutoring system for programming education. The ALPUS system can infer user's intentions from buggy codes in addition to detecting logical errors by means of knowledge-based reasoning. ALPUS uses four kinds of programming knowledge: 1) knowledge on algorithms, 2) Knowledge on programming techniques, 3) Knowledge on a programming language, and 4) Knowledge on logical errors. These knowledge are organized in a hierarchical procedure graph (HPG) as a multi-use knowledge base. The knowledge on logical errors was obtained by means of cognitive experiments. The student model is built by means of the results of ALPUS and interactions between a student and the system. Teaching is done based on the student model. Because the ITS subsystem, i.e., TUTOR, is embedded within the intelligent programming environment interactions for creating the student model could be minimized. Although the current system deals with the PASCAL language, most of the knowledge is applicable to those of procedure-oriented programming languages. The INTELLITUTOR system was implemented in the frame-based knowledge engineering environment ZERO and working on a UNIX workstation for system evaluation.