# Tag Info

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The statement $X\vDash Y$ means "every assignment to the variables that makes $X$ true also makes $Y$ true." Or to put it another way, "There is no assignment of variables that makes $X$ true but fails to make $Y$ true." Well, there's no assignment of variables that makes $A\land\neg A$ true, so there's certianly no assignment that makes $A\land\neg A$ true ...

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Most logical systems in use are automated enough in principle. That is, there are algorithms which find the proof of a statement, if such a proof exists. The problem is computational complexity. Such algorithms are very, very, very, very, very slow. We only know efficient algorithms for special, easy cases. More generally, knowledge representation is not ...

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In §3.2 they distinguish between the following four grammatical categories, with some examples: Predicates: Woman, Rich, Beautiful, Bankrupt Relations: LivesAt, HadAnAffairWith, Loves Functions: fatherOf, bestFriendOf, ceoOf Individual constants: maryJones, johnQSmith, tomsHouse In the background they have first-order logic with identity, which means ...

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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-...

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XML is nothing more than a well-defined way to store trees of strings. Since even plain strings can encode everything you can encode in practice (i.e. countable sets), yes, XML can "model" everything. But that's nothing special. The popularity of XML is probably due to it being standardized and the amount of tool support that has developed. There is no ...

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Semantic Web is a set of technologies that want to make the data on the web readable and understood by machines. The domain that semantic web is the web. Therefore the URI is in the bottom of the technologies stack. Semantic Network is a graph model to store the information. If you can model your data as a graph with node and edge, you can think it as a ...

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The λ-calculus was invented to be a logic and foundation of mathematics (1-4). The most well-known logic to use λ-calculus for formulae (as opposed to proofs in the Curry-Howard approach) is HOL (= Higher-Order Logic). The most well-developed implementation of HOL is Isabelle/HOL (5). To the extent that you believe logic can represent ...

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Network flow has been used for all sorts of interesting and surprising tasks in computer vision and image processing. For instance, it has been used for image segmentation, image stitching, seam carving, image denoising, stereo image correspondence, and more. See, e.g., https://en.wikipedia.org/wiki/Graph_cuts_in_computer_vision, What's the ...

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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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DBpedia provides structured information from Wikipedia. It uses RDF, and is one of the most known Linked Data datasets. Also of interest (but not using information from Wikipedia) may be Freebase and OpenCyc.

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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 ...

3

Consider the expression $+(x,\times(y,y))$, which is the FOL way to write $x+(y\cdot y)$. If I substitute $x=3$ and $y=5$ and do the arithmetic over the integers, what do I get? I need to evaluate the expression recursively. In order to evaluate $+(x,\times(y,y))$, I need to evaluate $x$, to evaluate $\times(y,y)$, and then to combine them using the ...

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Semantic Networks are in no way the same as ontologies. The accepted answer is therefore very misleading. Semantic networks (Quillian 1968) and semantic frames (Minsky 1975) emerged earlier than ontologies, and they were lacking a formal semantics despite the fact that they had semantic in the name. This is some kind of a fun fact among logicians: a ...

3

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 ...

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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 ...

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You are probably talking about homomorphisms from logic, i.e. homomorphisms that just preserve your functions and relations: https://en.wikipedia.org/wiki/Structure_(mathematical_logic) I'm a bit suspicious about why your instructor bothered to give you these concepts in the intro course. I also suspect you just need to understand a difference between ...

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One hexadecimal digit contains 4 binary digits. You can compute this as follows: $\log_2 16 = 4$. Alternatively, $2^4 = 16$. So the minimal memory element will contain 4 bits' worth of information. This also works when the number of states is not a power of 2, but you have to be more flexible in your interpretation.

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They are mostly synonymous. In that profession you can be called, or call yourself, a coder, a programmer, a software developer, or a software engineer. They all do the same job. If you call yourself an "engineer", then in many jurisdictions you would have to have training, pass some stringent exams, and may have legal responsibilities for the results - ...

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I would encourage you to start with this survey paper by Nickel et al.: https://arxiv.org/abs/1503.00759 Recent notable models: ComplEx-N3: Lacroix et al. Canonical Tensor Decomposition for Knowledge Base Completion. 2018. HypER: Balazevic et al. Hypernetwork Knowledge Graph Embeddings. 2018. TuckER: Balazevic et al. TuckER: Tensor Factorization for ...

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No, probably not. I think you're expecting too much from the current state of the art in word embeddings. Word embeddings don't magically capture all semantic knowledge. They don't reflect perfect understanding of the language. Instead, they're just useful mappings where similar words often have similar embeddings. Moreover, the way word embeddings are ...

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As you say, relational databases are designed for, essentially, answering queries. Rete, I would rather say, is designed for the specific task of materialized view maintenance (i.e., keeping updated the results of a query, once new changes to the data are applied). Of course, you can answer queries by building a materialized view of them, and this is why SQL ...

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The ontologies that are used today are mostly based on Description Logics (DLs). The basic building blocks of DLs consists of concepts and relationships between concepts where a concept represents a set of individuals (elements) and a relationship states that an individual of one set is related to an individual of another set. A good book in this regards ...

1

You're description is pretty accurate. There is no formal definition or precise meaning coming from a high level. There are only formal definitions in specific fields such as information theory for Information (bits) and knowledge such as in cognitive architectures. Data doesn't have a precise meaning either, haven't seen a formal model of that in any case.

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The code in Listing 1 represents my attempt to test the claim. I have simplified the classes, while retaining that ability to test the original claim, which is repeated here: The Haskell code given so far is complete and type checked, explaining the entire refined concept hierarchies. With instantiations for types of boathouses and houseboats, values can be ...

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They are synonymous. Programming is the act of writing "source code". Coding is just short for "source code" writing. As someone else stated, nobody has ownership of official definitions of these slang terms, so take any answer with a grain of salt. If you had, however, asked me the difference between "programming" and "software engineering", then I'd say ...

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It highly depends on what is the domain you are working on, i.e. why do you need to generate Java Source code anyway?. Can you explain better what knowledge do you have stored in your knowledge base?. The most "formal" method I can think of is by using the Java grammar and generate and abstract syntax tree as you mentioned. But it may or may not be ...

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For this discussion, I'll use classical first-order logic. I'll interpret your term "first-class citizens" to mean those objects which can be quantified over or passed as arguments to predicates and functions. The examples provided below are toy examples, purely for expository purposes. Have a look at the leading AI textbook which gives a much more extensive,...

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Use some form of metamodelling : The outputs are represented as abstract syntax trees (ASTs): and constructed by a decoder with a dynamically-determined modular structure paralleling the structure of the output tree. References Modelling homogeneous generative meta-programming Abstract Syntax Networks for Code Generation and Semantic Parsing ...

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Some more detail can be found p97. Here "ontologies" are basically encodings of database contents (which represent cyber attacks, incidents, and malicious/ impacted software programs) parseable by external sources, e.g. ACT-R. The event data management system keeps track of (real) attacks/ incidents, or possibly simulated ones. TENA is a Testing and Training ...

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