Three Highly Parallel Computer Architectures and Their Suitability for Three Representative Artificial Intelligence Problems

Virtually all current Artificial Intelligence (AI) applications are designed to run on sequential (von Neumann) computer architectures. As a result, current systems do not scale up. As knowledge is added to these systems, a point is reached where their performance quickly degrades. The performance of a von Neumann machine is limited by the bandwidth between memory and processor (the von Neumann bottleneck). The bottleneck is avoided by distributing the processing power across the memory of the computer. In this scheme the memory becomes the processor (a smart memory ). This paper highlights the relationship between three representative AI application domains, namely knowledge representation, rule-based expert systems, and vision, and their parallel hardware realizations. Three machines, covering a wide range of fundamental properties of parallel processors, namely module granularity, concurrency control, and communication geometry, are reviewed: the Connection Machine (a fine-grained SIMD hypercube), DADO (a medium-grained MIMD/SIMD/MSIMD tree-machine), and the Butterfly (a coarse-grained MIMD Butterflyswitch machine)

Developing and Measuring Parallel Rule-Based Systems in a Functional Programming Environment

This thesis investigates the suitability of using functional programming for building parallel rule-based systems. A functional version of the well known rule-based system OPS5 was implemented, and there is a discussion on the suitability of functional languages for both building compilers and manipulating state. Functional languages can be used to build compilers that reflect the structure of the original grammar of a language and are, therefore, very suitable. Particular attention is paid to the state requirements and the state manipulation structures of applications such as a rule-based system because, traditionally, functional languages have been considered unable to manipulate state. From the implementation work, issues have arisen that are important for functional programming as a whole. They are in the areas of algorithms and data structures and development environments. There is a more general discussion of state and state manipulation in functional programs and how theoretical work, such as monads, can be used. Techniques for how descriptions of graph algorithms may be interpreted more abstractly to build functional graph algorithms are presented. Beyond the scope of programming, there are issues relating both to the functional language interaction with the operating system and to tools, such as debugging and measurement tools, which help programmers write efficient programs. In both of these areas functional systems are lacking. To address the complete lack of measurement tools for functional languages, a profiling technique was designed which can accurately measure the number of calls to a function , the time spent in a function, and the amount of heap space used by a function. From this design, a profiler was developed for higher-order, lazy, functional languages which allows the programmer to measure and verify the behaviour of a program. This profiling technique is designed primarily for application programmers rather than functional language implementors, and the results presented by the profiler directly reflect the lexical scope of the original program rather than some run-time representation. Finally, there is a discussion of generally available techniques for parallelizing functional programs in order that they may execute on a parallel machine. The techniques which are easier for the parallel systems builder to implement are shown to be least suitable for large functional applications. Those techniques that best suit functional programmers are not yet generally available and usable

SMILE/ MARVEL: Two Approaches to Knowledge-Based Programming Environments

This technical report consists of three related papers in the area of intelligent assistance for software development and maintenance. Intelligent Assistance without Artificial Intelligence describes SMILE, a software engineering environment that assists teams of programmers without using AI technology. An Architecture for Intelligent Assistance in Software Development presents an AI approach to generalizing the capabilities of SMILE. Granularity Issues in a Knowledge-Based Programming Environment briefly describes MARVEL, an intelligent assistant based on this AI approach, and compares it to SMILE

A Survey on IT-Techniques for a Dynamic Emergency Management in Large Infrastructures

This deliverable is a survey on the IT techniques that are relevant to the three use cases of the project EMILI. It describes the state-of-the-art in four complementary IT areas: Data cleansing, supervisory control and data acquisition, wireless sensor networks and complex event processing. Even though the deliverable’s authors have tried to avoid a too technical language and have tried to explain every concept referred to, the deliverable might seem rather technical to readers so far little familiar with the techniques it describes

A knowledge-based approach for the extraction of machining features from solid models

Computer understanding of machining features such as holes and pockets is essential for bridging the communication gap between Computer Aided Design and Computer Aided Manufacture. This thesis describes a prototype machining feature extraction system that is implemented by integrating the VAX-OPS5 rule-based artificial intelligence environment with the PADL-2 solid modeller. Specification of original stock and finished part geometry within the solid modeller is followed by determination of the nominal surface boundary of the corresponding cavity volume model by means of Boolean subtraction and boundary evaluation. The boundary model of the cavity volume is managed by using winged-edge and frame-based data structures. Machining features are extracted using two methods : (1) automatic feature recognition, and (2) machine learning of features for subsequent recognition. [Continues.

MODELING DYNAMICS OF DATABASES WITH RELATIONAL DISCRETE EVENT SYSTEMS AND MODELS

Behavior of relational databases is studied within the framework of Relational Discrete Event Systems (RDESes) and Models (RDEMs). Three behavior specification methods based on production systems, recurrence equations, and Petri nets are defined and their expressive powers are compared. Production system RDEM is extended to support non-determinism, and various deterministic and non-deterministic production system interpreters are introduced and formally compared in terms of their expressive power. It is shown that the parallel deterministic interpreter has more expressive power than other interpreters including an OPS5-like interpreter. Since it is also parallel, this makes the parallel deterministic interpreter a very attractive interpreter for production systems.Information Systems Working Papers Serie

Working notes of the KI \u2796 Workshop on Agent Oriented Programming and Distributed Systems

Agent-oriented techniques are likely to be the next significant breakthrough in software development process. They provide a uniform approach throughout the analysis, design and implementation phases in the development life cycle. Agent-oriented techniques are a natural extension to object-oriented techniques, but while there is a whole pIethora of analysis and design methods in the object-oriented paradigm, very little work has been reported on design and analysis methods in the agent-oriented community. After surveying and examining a number of well-known object-oriented design and analysis methods, we argue that none of these methods, provide the adequate model for the design and analysis of multi-agent systems. Therefore, we propose a new agent-specific methodology that is based on and builds upon object-oriented methods. We identify three major models that need to be build during the development of multi-agent applications and describe the process of building these models

Third Conference on Artificial Intelligence for Space Applications, part 1

The application of artificial intelligence to spacecraft and aerospace systems is discussed. Expert systems, robotics, space station automation, fault diagnostics, parallel processing, knowledge representation, scheduling, man-machine interfaces and neural nets are among the topics discussed

Knowledge Based Systems: A Critical Survey of Major Concepts, Issues, and Techniques

This Working Paper Series entry presents a detailed survey of knowledge based systems. After being in a relatively dormant state for many years, only recently is Artificial Intelligence (AI) - that branch of computer science that attempts to have machines emulate intelligent behavior - accomplishing practical results. Most of these results can be attributed to the design and use of Knowledge-Based Systems, KBSs (or ecpert systems) - problem solving computer programs that can reach a level of performance comparable to that of a human expert in some specialized problem domain. These systems can act as a consultant for various requirements like medical diagnosis, military threat analysis, project risk assessment, etc. These systems possess knowledge to enable them to make intelligent desisions. They are, however, not meant to replace the human specialists in any particular domain. A critical survey of recent work in interactive KBSs is reported. A case study (MYCIN) of a KBS, a list of existing KBSs, and an introduction to the Japanese Fifth Generation Computer Project are provided as appendices. Finally, an extensive set of KBS-related references is provided at the end of the report