کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6853498 | 659007 | 2015 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Vector space architecture for emergent interoperability of systems by learning from demonstration
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
The rapid integration of physical systems with cyberspace infrastructure, the so-called Internet of Things, is likely to have a significant effect on how people interact with the physical environment and design information and communication systems. Internet-connected systems are expected to vastly outnumber people on the planet in the near future, leading to grand challenges in software engineering and automation in application domains involving complex and evolving systems. Several decades of artificial intelligence research suggests that conventional approaches to making such systems automatically interoperable using handcrafted “semantic” descriptions of services and information are difficult to apply. In this paper we outline a bioinspired learning approach to creating interoperable systems, which does not require handcrafted semantic descriptions and rules. Instead, the idea is that a functioning system (of systems) can emerge from an initial pseudorandom state through learning from examples, provided that each component conforms to a set of information coding rules. We combine a binary vector symbolic architecture (VSA) with an associative memory known as sparse distributed memory (SDM) to model context-dependent prediction by learning from examples. We present simulation results demonstrating that the proposed architecture can enable system interoperability by learning, for example by human demonstration.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biologically Inspired Cognitive Architectures - Volume 11, January 2015, Pages 53-64
Journal: Biologically Inspired Cognitive Architectures - Volume 11, January 2015, Pages 53-64
نویسندگان
Blerim Emruli, Fredrik Sandin, Jerker Delsing,