Hiroyuki Yamauchi

Multi-layer logic—A predicate logic including data structure as knowledge representation language

A new generation computer is expected to be the knowledge processing system of the future. However, many aspects are yet unknown regarding this technology, and a number of fundamental concepts, directly concerning knowledge processing system design need investigation, such as knowledge, data, inference, communication, information management, learning, and human interface.These concepts are closely related to knowledge representation. In particular, methodology to materialize such concepts as above in computers are completely dependent upon them. Thus, knowledge representation is a key concept in the design of knowledge processing systems and, consequently, of new generation computer systems.Knowledge representation design is a very important task affecting the performance of new generation computer systems to be developed. We should first investigate the requirements for precise knowledge representation, considering its effects on system performance, then design knowledge representations to satisfy these requirements.This paper discusses (1) a new style of information processing, (2) requirements for knowledge representation and (3) a knowledge representation satisfying these requirements, a knowledge processing system designed on this basis and a new style of problem solving using this system.

Loose coupling of KAUS with existing RDBMSs

Abstract With the recent progress and popularization of computers and computer communications, the technology for the integrated use of distributed computer hardware and softwares through computer networks is becoming important. Especially, in the current paradigm of knowledge processing, it has become one of the main subjects to couple the knowledge based systems with remote or local database systems for their integrated and more intellectual use. We introduce a knowledge processing system KAUS (Knowledge Acquisition and Utilization System), which is a logic based system, and describe how to couple it loosely with existing relational database systems (RDBMSs). In loosely coupling, we take an approach to generate an intermediate language for the database access from the given query, translate it to the target RDB language then evaluate it in the RDBMS, and finally receive the result from the RDBMS. Queries implying database access are evaluated by the mixed use of interpretive and compiled method. We illustrate examples of coupling KAUS with a database system UNIFY which supports SQL and a personal database system dBaseIII which supports its own procedural language for data manipulation.

A Method and Language for Constructing Multiagent Systems

This paper describes a method to construct multiagent systems. The method proposed here is explored accounting for the Gibsons ecological view of information, i.e. affordance. We apply the idea of affordance not only to the reactive models of agents but also to the deliberative models of the agents. By this approach, we can avoid the frame problems that emerge from the dynamic environment including the agents mental world. We describe a basic representation scheme for agent modules which reflects the Gibsons view of information resources. As a system description language, we use knowledge processing language KAUS (knowledge acquisition and utilization system) based on first order logic and axiomatic set theory. We consider as an example the multi-strata modeling scheme for developing human-computer interactive problem solving systems that are essentially multiagent systems.

Incorporating Fuzzy Set Theory and Matrix Logic in Multi-layer Logic

This paper is concerned with a preliminary consideration to provide the formal specification of language of knowledge processing system SKAUS (Super Knowledge Acquisition and Utilization System) which incorporates uncertain knowledge processing and non-symbolic information processing units in the system. SKAUS is planned as a super set of KAUS developed by the authors. KAUS implement multi-layer logic (MLL for short) based on classical set theory. SKAUS is intended to have additional capabilities of KAUS, such as representing uncertain knowledge in the forms of language used in fuzzy set theory and probability theory. In addition to this extension, we try to incorporate matrix logic into our extension so as to process non-symbolic information in corporation with neural networks.