33 research outputs found

    Red gaming in support of the war on terrorism : Sandia Red Game report.

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    Developing Educational Software: a professional tool perspective

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    The selection, and use of educational software and its impact in schools are still controversial issues. In this paper we present an alternative conceptualisation of educational software based on considering the software as an instrument for teachers’ professional performance. We review previous work in the areas of the design, development and evaluation of educational software and of the process of educational innovation. The review of these four areas converges to demonstrate the need for knowing and considering the context of use of educational software and for understanding users' perspectives about its roles and possibilities and hence supports a consideration a perspective on educational software which sees it as a professional tool for teachers performance of their teaching role

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

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    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

    A Blackboard Integration of Manufacturing Databases Using an Intelligent Interface.

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    The explosion of computer applications into the world of manufacturing along functional lines has produced the often mentioned islands of automation. Although many issues and problems are involved in interfacing and integrating the databases that serve these applications, we can extract valuable data from these independent systems to provide important information to decision makers. This research resulted in the development of MIMIR (Multiple Integrated Manufacturing Information Resources), a decision support system based upon the blackboard architecture. The blackboard architecture extends the common expert system design to include multiple expert systems, termed Knowledge Sources (KS\u27s), which combine to solve problems too diverse or complex for conventional expert systems. Extending the architecture, MIMIR uniquely adds Data Sources (DS\u27s) to the conventional KS\u27s for problem decomposition and solution. Developed in Common LISP and CLOS, MIMIR can answer basic questions about the data in the remote databases and generate multiple queries for more complex questions. Seven partitions in MIMIR\u27s blackboard allow KS\u27s and DS\u27s to focus on specific levels of the problem decomposition. MIMIR relies on an intelligent interface to translate an internal LISP-based SQL-like query into a valid SQL query string. This query is then be submitted to an external relational database and results are returned to the blackboard environment. While MIMIR is currently limited to SQL-accessible relational databases, the architecture can be extended to support interfaces to other data formats

    Computational Intelligence in Archaeology. State of the Art

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    DESIGN AND VERIFICATION OF AUTONOMOUS SYSTEMS IN THE PRESENCE OF UNCERTAINTIES

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    Autonomous Systems offer hope towards moving away from mechanized, unsafe, manual, often inefficient practices. The last decade has seen several small, but important, steps towards making this dream into reality. These advancements have helped us to achieve limited autonomy in several places, such as, driving, factory floors, surgeries, wearables, and home assistants, etc. Nevertheless, autonomous systems are required to operate in a wide range of environments with uncertainties (viz., sensor errors, timing errors, dynamic nature of the environment, etc.). Such environmental uncertainties, even when present in small amounts, can have drastic impact on the safety of the system—thus hampering the goal of achieving higher degree of autonomy, especially in safety critical domains. To this end, the dissertation shall discuss formaltechniques that are able to verify and design autonomous systems for safety, even under the presence of such uncertainties, allowing for their trustworthy deployment in the real world. Specifically, the dissertation shall discuss monitoring techniques for autonomous systems from available (noisy) logs, and safety-verification techniques of autonomous system controllers under timing uncertainties. Secondly, using heterogeneous learning-based cloud computing models that can balance uncertainty in output and computation cost, the dissertation will present techniques for designing safe and performance-optimal autonomous systems.Doctor of Philosoph
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