Initial thoughts on rapid prototyping techniques

This paper sets some context, raises issues, and provides our initial thinking on the characteristics of effective rapid prototyping techniques.After discussing the role rapid prototyping techniques can play in the software lifecycle, the paper looks at possible technical approaches including: heavily parameterized models, reusable software, rapid prototyping languages, prefabrication techniques for system generation, and reconfigurable test harnesses.The paper concludes that a multi-faceted approach to rapid prototyping techniques is needed if we are to address a broad range of applications successfully -- no single technical approach suffices for all potentially desirable applications

A New Constructivist AI: From Manual Methods to Self-Constructive Systems

The development of artificial intelligence (AI) systems has to date been largely one of manual labor. This constructionist approach to AI has resulted in systems with limited-domain application and severe performance brittleness. No AI architecture to date incorporates, in a single system, the many features that make natural intelligence general-purpose, including system-wide attention, analogy-making, system-wide learning, and various other complex transversal functions. Going beyond current AI systems will require significantly more complex system architecture than attempted to date. The heavy reliance on direct human specification and intervention in constructionist AI brings severe theoretical and practical limitations to any system built that way. One way to address the challenge of artificial general intelligence (AGI) is replacing a top-down architectural design approach with methods that allow the system to manage its own growth. This calls for a fundamental shift from hand-crafting to self-organizing architectures and self-generated code – what we call a constructivist AI approach, in reference to the self-constructive principles on which it must be based. Methodologies employed for constructivist AI will be very different from today’s software development methods; instead of relying on direct design of mental functions and their implementation in a cog- nitive architecture, they must address the principles – the “seeds” – from which a cognitive architecture can automatically grow. In this paper I describe the argument in detail and examine some of the implications of this impending paradigm shift

Software safety : a definition and some preliminary thoughts

Software safety is the subject of a research project in its initial stages at the University of California Irvine. This research deals with critical real-time software where the cost of an error is high, e.g. human life. In this paper software techniques having a bearing on safety are described and evaluated. Initial definitions of software safety concepts are presented along with some preliminary thoughts and research questions