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I have read many papers and books about ontologies and I am trying to figure out that how they are used in a real project?

For example how the ontology for a soccer player robot can be defined and used with a cognitive architecture in order to make it intelligent?

Are ontologies relations between terms in that domain of knowledge ( for example relation between the ball and foot word and physical rules definition and their relation with the foot and ball movement , ...) or relations between tactics , strategies and different mixtures of tactics ?

Are there any clear examples of ontology usage in real projects and their combining usage with the cognitive architectures like ACT-R for augmenting the cognitive architecture?

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I don't know about robotics, but ontologies are part of the standard toolkit for modern expert systems, especially those with a natural language processing component.

For example, consider the process of performing literature searches for systematic reviews in medicine. Of the millions of medical studies out there, reviewers need to find the 20 or so high-quality randomised control trial studies which are relevant to the clinical question that they want to answer. This is a classic needle-in-a-haystack problem, and computer scientists would like to build tools to aid the search.

Medical ontologies such as MeSH, ICD, and GALEN play a role in this, because they represent an "answer" to the question of what a given medical study is "about".

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IBM's question-answering system, Watson, used the ontology DBPedia in their evidence scoring algorithms to compete (and win) the Jeopardy Challenge.

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Ontology gives you a power to model, reason and manage complex data systems from different domains. For example Natural Language Processing (NLP), Molecular Biology and Bioinformatic, Wireless Sensor Networks, to name a few.

Considering semantic web (RDF-based) as a special use case of ontology-based systems, there are many companies and commercials on that like Franz.Inc work on semantic web and Freebase (part of Google).

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Ontologies abstractly defined are "representation of knowledge": the object and their relations.

Basically the ontology represent the knowledge exploited by the "intelligent" agent.

Now in practice, ontologies can be used either as:

  • a structured knowledge representation for domain-specific databases

  • a structured data format for interoperability of different systems

  • a way to structure an object hierarchy with a programming language for a target domain

Cognitive architecture, means that there is a decision architecture that nativey exploits knowledge representation and inteligent inference based on it, as it is for example the case with BDI (Belief Desire Intention) agents that use modal logic.

In the field of Multiagent Systems, you can check the many industrial project based on JADE or JACK architecure, which use ontologies and cognitive architectures.

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There is a fairly strong connection between ontologies and APIs. An ontology can be regarded roughly as a word-based API. Many are associated with web-based languages in XML part of the so-called semantic web also defined here. Tim Berners Lee, the inventor of the web, has strongly advocated the semantic web & has written on it. Here are two simple examples that are easily understood w.r.t. blogs.

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