Propagation techniques in WAM-based architectures : the FIDO-III approach

In this paper we develop techniques to implement finite domain constraints into the Warren Abstract Machine (WAM) to solve large combinatorial problems effciently. The WAM is the de facto standard model for compiling PROLOG. The FIDO system ("FInite Domain\u27;) provides the same functionality as the finite domain part of CHIP. The extension includes the integration of several new variable types (suspended variables, domain variables and suspended domain variables) into the WAM. The "firing conditions\u27; are lookahead and forward control schemes known from CHIP. We have developed a constraint model where the constraint is divided into constraint initialization code, constraint testing code and constraint body. Furthermore, we supply a deeply integrated WAM builtin to realize the first fail principle. Besides the summary of the important theoretical results, the specification of the compilation process in the WAM Compilation Scheme is given. We also present a simple graphical analysis method to estimate the computational burden of lookahead and forward constraints. The work is an instance of exploring finite domain consistency techniques in logic programming belonging to the FIDO lab within the ARC-TEC project

Propagation techniques in WAM-based architectures : the FIDO-III approach

In this paper we develop techniques to implement finite domain constraints into the Warren Abstract Machine (WAM) to solve large combinatorial problems effciently. The WAM is the de facto standard model for compiling PROLOG. The FIDO system ("FInite Domain';) provides the same functionality as the finite domain part of CHIP. The extension includes the integration of several new variable types (suspended variables, domain variables and suspended domain variables) into the WAM. The "firing conditions'; are lookahead and forward control schemes known from CHIP. We have developed a constraint model where the constraint is divided into constraint initialization code, constraint testing code and constraint body. Furthermore, we supply a deeply integrated WAM builtin to realize the first fail principle. Besides the summary of the important theoretical results, the specification of the compilation process in the WAM Compilation Scheme is given. We also present a simple graphical analysis method to estimate the computational burden of lookahead and forward constraints. The work is an instance of exploring finite domain consistency techniques in logic programming belonging to the FIDO lab within the ARC-TEC project

Indexing principles for relational languages applied to PROLOG code generation

In this paper we propose an extensible, flexible, multi-argument indexing technique for relational languages. We present a compiler producing indexing header code for a PROLOG emulator based on the Warren Abstract Machine. We will show that our technique combines positive aspects of relational database methods and other existing WAM-based indexing schemes. All the indexing concepts introduced are implemented in LISP for the relational-functional programming language RELFUN

ColorPalette: A Knowledge-based system to select colors for a palette

This paper describes ColorPalette, a knowledge-based system to advise users in selecting colors for a palette used for computer screen design applications. Color selections and advice are based on principles of human computer interface design and color theory, gathered through both research and knowledge acquisition from a human expert. The user may put together various color combinations to form acceptable and successful palettes. The system consists of a color data-base of facts formulated from an HSV color model, a knowledge base that can reason about these colors and their relations to each other, and a set of rules based on the interface design and color theory research. Colors may be added to and removed from the palette as desired, as long as they meet the criteria of the knowledge-based system. The system may be called on to propose a sample palette with desired characteristics, or may be asked to suggest a color that is recommended to go with the current palette. An explanation facility is available to explain the system\u27s decisions to allow or restrict the adding of colors, and to explain why a certain color has been suggested. ColorPalette is written in Prolog, taking advantage of Prolog\u27s structural foundations, logic programming support, database management capabilities, and natural format for rule-based systems. ColorPalette has a simple command-line interface, with potential extensions to be able to support graphical selection of colors. It is implemented on an Apple Macintosh, and with such extensions would be able to take advantage of Color Quickdraw calls for interactive color selection and display

Neuere Entwicklungen der deklarativen KI-Programmierung : proceedings

The field of declarative AI programming is briefly characterized. Its recent developments in Germany are reflected by a workshop as part of the scientific congress KI-93 at the Berlin Humboldt University. Three tutorials introduce to the state of the art in deductive databases, the programming language Gödel, and the evolution of knowledge bases. Eleven contributed papers treat knowledge revision/program transformation, types, constraints, and type-constraint combinations

Artificial intelligence as writing: knowledge-based hypertext systems as a medium for communication

This thesis is an exploration of a new metaphor for artificial intelligence (AI). Traditionally, the computer within AI has been viewed as an agent, one with which the user engages in a conversation. More recently certain researchers have proposed the notion that artificial intelligence (and indeed computing in general) can be more appropriately seen as a form of writing. Initially this thesis reviews the literature in this area, and aspects of AI which support the approach. Features of writing are then described which show parallels with AI. This then allows us to take lessons from the history and development of both traditional writing and the new computer-based writing systems to inform the design of a new type of artificial intelligence system. A design based on these features, called Running Texts is presented through a number of small examples. Issues that arise from these and possible future developments, based on the implementation are then discussed. A rationale for users choosing to learn a system such as Running Texts is proposed, as benefits from the psychological and social implications of writing can be applied to AI systems, when they are seen as writing. The same parallels point out potential problems, and suggest new ways to see the relation between AI and thought