Patterns of Growth: Operationalizing Alexander's "Web Way of Thinking"

Christopher Alexander was often characterized - and sometimes seemed to characterize himself - as "sui generis," a radical and perhaps even eccentric thinker on architecture, technology, culture, and nature. That perception in turn has led many to dismiss Alexander's work as too idiosyncratic to be operationalized in the pragmatic world of planning and building. Here we show, however, that Alexander's core ideas have strong parallels in contemporary network science, mathematics, physics, and philosophy, and in the pragmatic world of technological design (including computer software). We highlight a remaining gap in translating Alexander's work into practical tools and strategies for implementation - a gap that is tantalizingly near to being bridged

The Many Functions of Discourse Particles: A Computational Model of Pragmatic Interpretation

We present a connectionist model for the interpretation of discourse\ud particles in real dialogues that is based on neuronal\ud principles of categorization (categorical perception, prototype\ud formation, contextual interpretation). It can be shown that\ud discourse particles operate just like other morphological and\ud lexical items with respect to interpretation processes. The description\ud proposed locates discourse particles in an elaborate\ud model of communication which incorporates many different\ud aspects of the communicative situation. We therefore also\ud attempt to explore the content of the category discourse particle.\ud We present a detailed analysis of the meaning assignment\ud problem and show that 80%– 90% correctness for unseen discourse\ud particles can be reached with the feature analysis provided.\ud Furthermore, we show that ‘analogical transfer’ from\ud one discourse particle to another is facilitated if prototypes\ud are computed and used as the basis for generalization. We\ud conclude that the interpretation processes which are a part of\ud the human cognitive system are very similar with respect to\ud different linguistic items. However, the analysis of discourse\ud particles shows clearly that any explanatory theory of language\ud needs to incorporate a theory of communication processes

Tailored retrieval of health information from the web for facilitating communication and empowerment of elderly people

A patient, nowadays, acquires health information from the Web mainly through a “human-to-machine” communication process with a generic search engine. This, in turn, affects, positively or negatively, his/her empowerment level and the “human-to-human” communication process that occurs between a patient and a healthcare professional such as a doctor. A generic communication process can be modelled by considering its syntactic-technical, semantic-meaning, and pragmatic-effectiveness levels and an efficacious communication occurs when all the communication levels are fully addressed. In the case of retrieval of health information from the Web, although a generic search engine is able to work at the syntactic-technical level, the semantic and pragmatic aspects are left to the user and this can be challenging, especially for elderly people. This work presents a custom search engine, FACILE, that works at the three communication levels and allows to overcome the challenges confronted during the search process. A patient can specify his/her information requirements in a simple way and FACILE will retrieve the “right” amount of Web content in a language that he/she can easily understand. This facilitates the comprehension of the found information and positively affects the empowerment process and communication with healthcare professionals

Expert systems and developing expertise: Implications of Artificial Intelligence for Education

This paper discusses a few issues in AI research with the aim of understanding whether the concepts or the tools of AI can be of use in education (see also Green, 1984). Most of the discussion focuses on natural language understanding, one aspect of the highly diverse field of AI.published or submitted for publicationis peer reviewe

Solving Bongard Problems with a Visual Language and Pragmatic Reasoning

More than 50 years ago Bongard introduced 100 visual concept learning problems as a testbed for intelligent vision systems. These problems are now known as Bongard problems. Although they are well known in the cognitive science and AI communities only moderate progress has been made towards building systems that can solve a substantial subset of them. In the system presented here, visual features are extracted through image processing and then translated into a symbolic visual vocabulary. We introduce a formal language that allows representing complex visual concepts based on this vocabulary. Using this language and Bayesian inference, complex visual concepts can be induced from the examples that are provided in each Bongard problem. Contrary to other concept learning problems the examples from which concepts are induced are not random in Bongard problems, instead they are carefully chosen to communicate the concept, hence requiring pragmatic reasoning. Taking pragmatic reasoning into account we find good agreement between the concepts with high posterior probability and the solutions formulated by Bongard himself. While this approach is far from solving all Bongard problems, it solves the biggest fraction yet

Contract Aware Components, 10 years after

The notion of contract aware components has been published roughly ten years ago and is now becoming mainstream in several fields where the usage of software components is seen as critical. The goal of this paper is to survey domains such as Embedded Systems or Service Oriented Architecture where the notion of contract aware components has been influential. For each of these domains we briefly describe what has been done with this idea and we discuss the remaining challenges.Comment: In Proceedings WCSI 2010, arXiv:1010.233

Parsing with parallelism : a spreading-activation model of inference processing during text understanding

The past decade of reseatch in Natural Language Processing has universally recognized that, since natural language input is almost always ambiguous with respect to its pragmatic implications, its syntactic parse, and even its lexical analysis (i.e., choice of correct word-sense for an ambiguous word), processing natural language input requires decisions about word meanings, syntactic structure, and pragmatic inferences. The lexical, syntactic, and pragmatic levels of inferencing are not as disparate as they have often been treated in both psychological and artificial intelligence research. In fact, these three levels of analysis interact to form a joint interpretation of text.ATLAST (A Three-level Language Analysis SysTem) is an implemented integration of human language understanding at the lexical, the syntactic, and the pragmatic levels. For psychological validity, ATLAST is based on results of experiments with human subjects. The ATLAST model uses a new architecture which was developed to incorporate three features: spreading activation memory, two-stage syntax, and parallel processing of syntax and semantics. It is also a new framework within which to interpret and tackle unsolved problems through implementation and experimentation

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N