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	<title>CiteULike: Tag aixi</title>
	<description>CiteULike: Tag aixi</description>


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        <rdf:li rdf:resource="http://www.citeulike.org/user/scis0000001/article/845318"/>
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<item rdf:about="http://www.citeulike.org/user/Scis0000002/article/1427499">
    <title>Agent based cooperative theory formation in pure mathematics</title>
    <link>http://www.citeulike.org/user/Scis0000002/article/1427499</link>
    <description>&lt;i&gt;(2000)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The HR program, Colton et al. (1999), performs theory formation in domains of pure mathematics. Given only minimal information about a domain, it invents concepts, make conjectures, proves theorems and finds counterexamples to false conjectures. We present here a multi-agent version of HR which may provide a model for how individual mathematicians perform separate investigations but communicate their results to the mathematical community, learning from others as they do. We detail the...</description>
    <dc:title>Agent based cooperative theory formation in pure mathematics</dc:title>

    <dc:creator>S Colton</dc:creator>
    <dc:creator>A Bundy</dc:creator>
    <dc:creator>T Walsh</dc:creator>
    <dc:source>(2000)</dc:source>
    <dc:date>2007-07-01T15:37:07-00:00</dc:date>
    <prism:publicationYear>2000</prism:publicationYear>
    <prism:category>agent-theory</prism:category>
    <prism:category>aixi</prism:category>
    <prism:category>argumentation</prism:category>
    <prism:category>argumentation-games</prism:category>
    <prism:category>argumentation-theory</prism:category>
    <prism:category>category-of-theories</prism:category>
    <prism:category>collaboration</prism:category>
    <prism:category>computability-logic</prism:category>
    <prism:category>computational-science</prism:category>
    <prism:category>dialogical-logic</prism:category>
    <prism:category>distributed</prism:category>
    <prism:category>distributed-operating-system</prism:category>
    <prism:category>experts</prism:category>
    <prism:category>extendability</prism:category>
    <prism:category>formal-digital-library</prism:category>
    <prism:category>formal-interoparability</prism:category>
    <prism:category>formal-problem-solving</prism:category>
    <prism:category>formal-science</prism:category>
    <prism:category>formation</prism:category>
    <prism:category>game-theory</prism:category>
    <prism:category>goedel-machine</prism:category>
    <prism:category>heterogeneous</prism:category>
    <prism:category>hyperefficiency</prism:category>
    <prism:category>hypernetworks</prism:category>
    <prism:category>iff</prism:category>
    <prism:category>interoperability</prism:category>
    <prism:category>logical-theories</prism:category>
    <prism:category>markets</prism:category>
    <prism:category>mathematics</prism:category>
    <prism:category>mechanized-mathematics</prism:category>
    <prism:category>metascience</prism:category>
    <prism:category>mkm</prism:category>
    <prism:category>oops</prism:category>
    <prism:category>optimality</prism:category>
    <prism:category>philosophy-of-science</prism:category>
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    <prism:category>scientific-community</prism:category>
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    <prism:category>socio-economic-systems</prism:category>
    <prism:category>theory-development</prism:category>
    <prism:category>unified-concept-theory</prism:category>
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<item rdf:about="http://www.citeulike.org/user/Scis0000002/article/1205241">
    <title>A Theory of Universal Artificial Intelligence based on Algorithmic Complexity</title>
    <link>http://www.citeulike.org/user/Scis0000002/article/1205241</link>
    <description>&lt;i&gt;ArXiv Computer Science e-prints (April 2000)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Decision theory formally solves the problem of rational agents in uncertain worlds if the true environmental prior probability distribution is known. Solomonoff's theory of universal induction formally solves the problem of sequence prediction for unknown prior distribution. We combine both ideas and get a parameterless theory of universal Artificial Intelligence. We give strong arguments that the resulting AIXI model is the most intelligent unbiased agent possible. We outline for a number of problem classes, including sequence prediction, strategic games, function minimization, reinforcement and supervised learning, how the AIXI model can formally solve them. The major drawback of the AIXI model is that it is uncomputable. To overcome this problem, we construct a modified algorithm AIXI-tl, which is still effectively more intelligent than any other time t and space l bounded agent. The computation time of AIXI-tl is of the order tx2^l. Other discussed topics are formal definitions of intelligence order relations, the horizon problem and relations of the AIXI theory to other AI approaches.</description>
    <dc:title>A Theory of Universal Artificial Intelligence based on Algorithmic Complexity</dc:title>

    <dc:creator>M Hutter</dc:creator>
    <dc:source>ArXiv Computer Science e-prints (April 2000)</dc:source>
    <dc:date>2007-04-03T23:13:43-00:00</dc:date>
    <prism:publicationYear>2000</prism:publicationYear>
    <prism:publicationName>ArXiv Computer Science e-prints</prism:publicationName>
    <prism:category>aixi</prism:category>
    <prism:category>computability-logic</prism:category>
    <prism:category>computational-games</prism:category>
    <prism:category>computational-intelligence</prism:category>
    <prism:category>gtm</prism:category>
    <prism:category>hypercomputability</prism:category>
    <prism:category>intelligence-order-relations</prism:category>
    <prism:category>power</prism:category>
    <prism:category>power-order-relations</prism:category>
    <prism:category>utm</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/845318">
    <title>Goedel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements</title>
    <link>http://www.citeulike.org/user/scis0000001/article/845318</link>
    <description>&lt;i&gt;(27 Dec 2004)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;A Goedel Machine is designed to solve arbitrary computational problems, such as maximizing the expected future reward of a robot in a possibly stochastic and reactive environment. Its initial software includes an axiomatic description of (1) the Goedel machine's hardware, (2) known aspects of the environment, (3) goals and rewards to be achieved, (4) costs of actions and computations, (5) the initial software itself (no circularity involved here). It also includes a possibly sub-optimal initial problem-solving policy and a proof searcher searching the space of computable proof techniques - that is, programs whose outputs are proofs. Unlike previous approaches, the self-referential Goedel machine will rewrite any part of its software (including axioms and proof searcher) as soon as it has found a proof that this will improve its future performance, given typically limited computational resources (its optimality notion is not restricted to the concept of asymptotic optimality). Self-rewrites represent globally optimal self-improvements (no local minima!), since provably none of all the alternative rewrites and proofs (that could be found in the future by continuing the proof search) is worth waiting for. To initialize the proof searcher we may use the recent Optimal Ordered Problem Solver.</description>
    <dc:title>Goedel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements</dc:title>

    <dc:creator>Juergen Schmidhuber</dc:creator>
    <dc:source>(27 Dec 2004)</dc:source>
    <dc:date>2006-09-15T13:12:04-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:category>adaptability</prism:category>
    <prism:category>aixi</prism:category>
    <prism:category>all-logical-theories</prism:category>
    <prism:category>atp</prism:category>
    <prism:category>autonomic-computing</prism:category>
    <prism:category>bias</prism:category>
    <prism:category>biops</prism:category>
    <prism:category>chu-space</prism:category>
    <prism:category>computability-logic</prism:category>
    <prism:category>computational-epistemology</prism:category>
    <prism:category>computational-learning</prism:category>
    <prism:category>computational-mathematics</prism:category>
    <prism:category>computational-science</prism:category>
    <prism:category>domain-theory</prism:category>
    <prism:category>dynamics</prism:category>
    <prism:category>efficiency</prism:category>
    <prism:category>formal-development</prism:category>
    <prism:category>formal-system</prism:category>
    <prism:category>generalized-kolmogorov-complexity</prism:category>
    <prism:category>goedel-machine</prism:category>
    <prism:category>gtm</prism:category>
    <prism:category>iff</prism:category>
    <prism:category>inference</prism:category>
    <prism:category>inference-dynamics</prism:category>
    <prism:category>interactivity</prism:category>
    <prism:category>lattice-of-theories</prism:category>
    <prism:category>least-time</prism:category>
    <prism:category>machine-learning</prism:category>
    <prism:category>metaevolution</prism:category>
    <prism:category>metalogic-programming</prism:category>
    <prism:category>metalogics</prism:category>
    <prism:category>metascience</prism:category>
    <prism:category>model-selection</prism:category>
    <prism:category>oops</prism:category>
    <prism:category>optimality</prism:category>
    <prism:category>paraconsistency</prism:category>
    <prism:category>problem-solving</prism:category>
    <prism:category>proof-search</prism:category>
    <prism:category>reinforcement-learning</prism:category>
    <prism:category>resource-allocation</prism:category>
    <prism:category>robotics</prism:category>
    <prism:category>searching</prism:category>
    <prism:category>self-adaptation</prism:category>
    <prism:category>self-managing</prism:category>
    <prism:category>self-reference</prism:category>
    <prism:category>semweb</prism:category>
    <prism:category>speed-prior</prism:category>
    <prism:category>survivability</prism:category>
    <prism:category>temporal-logic</prism:category>
    <prism:category>universality</prism:category>
    <prism:category>universal-search</prism:category>
    <prism:category>utility</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/849822">
    <title>Computability Logic: a formal theory of interaction</title>
    <link>http://www.citeulike.org/user/scis0000001/article/849822</link>
    <description>&lt;i&gt;(10 Dec 2004)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Computability logic is a formal theory of (interactive) computability in the same sense as classical logic is a formal theory of truth. This approach was initiated very recently in &#34;Introduction to computability logic&#34; (Annals of Pure and Applied Logic 123 (2003), pp.1-99). The present paper reintroduces computability logic in a more compact and less technical way. It is written in a semitutorial style with a general computer science, logic or mathematics audience in mind. An Internet source on the subject is available at &#60;a href=&#34;http://www.cis.upenn.edu/~giorgi/cl.html&#34;&#62;this http URL&#60;/a&#62;, and additional material at &#60;a href=&#34;http://www.csc.villanova.edu/~japaridz/CL/gsoll.html&#34;&#62;this http URL&#60;/a&#62; .</description>
    <dc:title>Computability Logic: a formal theory of interaction</dc:title>

    <dc:creator>Giorgi Japaridze</dc:creator>
    <dc:source>(10 Dec 2004)</dc:source>
    <dc:date>2006-09-19T15:36:25-00:00</dc:date>
    <prism:publicationYear>2004</prism:publicationYear>
    <prism:category>abstract-state-machines</prism:category>
    <prism:category>adaptability</prism:category>
    <prism:category>aixi</prism:category>
    <prism:category>all-logical-theories</prism:category>
    <prism:category>behavior</prism:category>
    <prism:category>chu-space</prism:category>
    <prism:category>classical-logic</prism:category>
    <prism:category>computability</prism:category>
    <prism:category>computability-logic</prism:category>
    <prism:category>computational-epistemology</prism:category>
    <prism:category>dynamics</prism:category>
    <prism:category>formal-theory</prism:category>
    <prism:category>iff</prism:category>
    <prism:category>interaction</prism:category>
    <prism:category>interactivity</prism:category>
    <prism:category>interference</prism:category>
    <prism:category>intuitionistic-logic</prism:category>
    <prism:category>linear-logic</prism:category>
    <prism:category>logic</prism:category>
    <prism:category>relativity</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/769988">
    <title>Interactive Computation: The New Paradigm</title>
    <link>http://www.citeulike.org/user/scis0000001/article/769988</link>
    <description>&lt;i&gt;&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The interaction paradigm provides a new conceptualization of computational phenomena that emphasizes interaction rather than algorithms, thus reflecting the shift in technology from number-crunching on mainframes to distributed intelligent networks with graphical user interfaces. Goldin, Smolka, and Wegner have structured the 18 contributions from distinguished researchers into four sections: &#34;Introduction&#34;, consisting of three chapters that explore and summarize the fundamentals of interactive computation; &#34;Theory&#34; with six chapters, each discussing a specific aspect of interaction; &#34;Applications&#34; showing in five chapters how this principle is applied in various subdisciplines of computer science; and &#34;New Directions&#34; presenting four multidisciplinary applications beyond computer science. The book challenges traditional Turing machine-based answers to fundamental questions relating to problem solving and the scope of computation. Assuming the reader has only an undergraduate-level background in computer science, it serves as an introduction to this increasingly important discipline.</description>
    <dc:title>Interactive Computation: The New Paradigm</dc:title>

    <dc:creator>Dina Goldin</dc:creator>
    <dc:creator>Scott Smolka</dc:creator>
    <dc:creator>Peter Wegner</dc:creator>
    <dc:date>2006-07-23T06:09:01-00:00</dc:date>
    <prism:publisher>Springer</prism:publisher>
    <prism:category>adaptability</prism:category>
    <prism:category>aixi</prism:category>
    <prism:category>behavior</prism:category>
    <prism:category>chu-space</prism:category>
    <prism:category>computability</prism:category>
    <prism:category>computability-logic</prism:category>
    <prism:category>computational-epistemology</prism:category>
    <prism:category>dynamics</prism:category>
    <prism:category>iff</prism:category>
    <prism:category>interactivity</prism:category>
    <prism:category>interference</prism:category>
    <prism:category>paraconsistency</prism:category>
    <prism:category>relativity</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/821144">
    <title>Meaning in Motion</title>
    <link>http://www.citeulike.org/user/scis0000001/article/821144</link>
    <description>&lt;i&gt;(2000)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;The paper sketches the place of dynamic semantics within a broader picture of developments in philosophical and linguistic theories of meaning. Some basic concepts of dynamic semantics are illustrated by means of a detailed analysis of anaphoric definite and indefinite descriptions, which are treated as contextually dependent quantificational expressions. It is shown how a dynamic view sheds new light on the contextual nature of interpretation, on the di#erence between monologue and...</description>
    <dc:title>Meaning in Motion</dc:title>

    <dc:creator>Jeroen Groenendijk</dc:creator>
    <dc:creator>Martin Stokhof</dc:creator>
    <dc:source>(2000)</dc:source>
    <dc:date>2006-08-29T13:37:39-00:00</dc:date>
    <prism:publicationYear>2000</prism:publicationYear>
    <prism:category>aixi</prism:category>
    <prism:category>chu-space</prism:category>
    <prism:category>computability-logic</prism:category>
    <prism:category>context-relativity</prism:category>
    <prism:category>dynamics</prism:category>
    <prism:category>interactivity</prism:category>
    <prism:category>interference</prism:category>
    <prism:category>meaning</prism:category>
    <prism:category>relativity</prism:category>
    <prism:category>semantics</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/786765">
    <title>A Gentle Introduction to The Universal Algorithmic Agent AIXI</title>
    <link>http://www.citeulike.org/user/scis0000001/article/786765</link>
    <description>&lt;i&gt;No. IDSIA-01-03. (2003)&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Decision theory formally solves the problem of rational agents in uncertain worlds if the true environmental prior probability distribution is known. Solomonoff's theory of universal induction formally solves the problem of sequence prediction for unknown prior distribution. We combine both ideas and get a parameterless theory of universal Artificial Intelligence. We give strong arguments that the resulting AIXI model is the most intelligent unbiased agent possible. We outline for a number of...</description>
    <dc:title>A Gentle Introduction to The Universal Algorithmic Agent AIXI</dc:title>

    <dc:creator>Marcus Hutter</dc:creator>
    <dc:source>No. IDSIA-01-03. (2003)</dc:source>
    <dc:date>2006-08-05T09:05:30-00:00</dc:date>
    <prism:publicationYear>2003</prism:publicationYear>
    <prism:number>IDSIA-01-03</prism:number>
    <prism:category>adaptability</prism:category>
    <prism:category>aixi</prism:category>
    <prism:category>al</prism:category>
    <prism:category>artificial-physics</prism:category>
    <prism:category>complexity</prism:category>
    <prism:category>computability-logic</prism:category>
    <prism:category>computational-epistemology</prism:category>
    <prism:category>emergence</prism:category>
    <prism:category>formation</prism:category>
    <prism:category>iff</prism:category>
    <prism:category>inductive-inference</prism:category>
    <prism:category>intelligence-order-relations</prism:category>
    <prism:category>interactivity</prism:category>
    <prism:category>machine-learning</prism:category>
    <prism:category>model</prism:category>
    <prism:category>model-selection</prism:category>
    <prism:category>order</prism:category>
    <prism:category>ordering</prism:category>
    <prism:category>paraconsistency</prism:category>
    <prism:category>prequential</prism:category>
    <prism:category>taxanomy</prism:category>
    <prism:category>uai</prism:category>
    <prism:category>universality</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/997769">
    <title>Observations on Prequential Analysis</title>
    <link>http://www.citeulike.org/user/scis0000001/article/997769</link>
    <description>&lt;i&gt;&lt;/i&gt;&lt;br /&gt;&lt;br /&gt;Prequential Analysis is an approach to statistics where inference methods, or models, are viewed as forecasting systems, and their quality is judged solely by the observed success of the forecasts they make.</description>
    <dc:title>Observations on Prequential Analysis</dc:title>

    <dc:creator>Jukka En</dc:creator>
    <dc:date>2006-12-16T15:35:13-00:00</dc:date>
    <prism:category>aixi</prism:category>
    <prism:category>gales</prism:category>
    <prism:category>prediction</prism:category>
    <prism:category>prequential</prism:category>
    <prism:category>statistics</prism:category>
    <prism:category>survivability</prism:category>
</item>



<item rdf:about="http://www.citeulike.org/user/scis0000001/article/1198001">
    <title>Universal data compression and portfolio selection</title>
    <link>http://www.citeulike.org/user/scis0000001/article/1198001</link>
    <description>&lt;i&gt;(1996)&lt;/i&gt;</description>
    <dc:title>Universal data compression and portfolio selection</dc:title>

    <dc:creator>TM Cover</dc:creator>
    <dc:source>(1996)</dc:source>
    <dc:date>2007-03-30T13:42:08-00:00</dc:date>
    <prism:publicationYear>1996</prism:publicationYear>
    <prism:issn>0272-5428</prism:issn>
    <prism:publisher>IEEE Computer Society</prism:publisher>
    <prism:category>aixi</prism:category>
    <prism:category>algorithmic-information-theory</prism:category>
    <prism:category>computational-economics</prism:category>
    <prism:category>computational-epistemology</prism:category>
    <prism:category>duality</prism:category>
    <prism:category>investment-theory</prism:category>
    <prism:category>portfolio-selection</prism:category>
</item>



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