An introduction to universal artificial intelligence:
"An Introduction to Universal Artificial Intelligence provides a gentle introduction to Universal Artificial Intelligence (UAI), a theory that provides a formal underpinning of what it means for an agent to act intelligently in a general class of environments. First presented in Universal Artif...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press
2024
|
| Ausgabe: | First edition |
| Schriftenreihe: | Chapman & Hall/CRC artificial intelligence and robotics series
|
| Schlagworte: | |
| Zusammenfassung: | "An Introduction to Universal Artificial Intelligence provides a gentle introduction to Universal Artificial Intelligence (UAI), a theory that provides a formal underpinning of what it means for an agent to act intelligently in a general class of environments. First presented in Universal Artificial Intelligence (Hutter, 2004), UAI presents a model in which most other problems in AI can be presented, and unifies ideas from sequential decision theory, Bayesian inference and information theory to construct AIXI, an optimal reinforcement learning agent that learns to act optimally in unknown environments. AIXI represents a theoretical bound on intelligent behaviour, and so we also discuss tractable approximations of this optimal agent. The book covers important practical approaches including efficient Bayesian updating with context tree weighting, and stochastic planning, approximated by sampling with Monte Carlo tree search. Algorithms are also included for the reader to implement, along with experimental results to compare against. This serves to approximate AIXI, as well as being used in state-of-the-art approaches in AI today. The book ends with a philosophical discussion of AGI covering the following key questions: Should intelligent agents be constructed at all, is it inevitable that they will be constructed, and is it dangerous to do so? This text is suitable for late undergraduates and includes an extensive background chapter to fill in the assumed mathematical background"-- |
| Beschreibung: | xix, 496 Seiten Illustrationen, Diagramme |
| ISBN: | 9781032607153 9781032607023 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV049753388 | ||
| 003 | DE-604 | ||
| 005 | 20240828 | ||
| 007 | t | ||
| 008 | 240624s2024 a||| |||| 00||| eng d | ||
| 020 | |a 9781032607153 |c hbk |9 978-1-032-60715-3 | ||
| 020 | |a 9781032607023 |c pbk |9 978-1-032-60702-3 | ||
| 035 | |a (OCoLC)1424992374 | ||
| 035 | |a (DE-599)BVBBV049753388 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-29T |a DE-188 |a DE-522 |a DE-83 |a DE-862 | ||
| 084 | |a ST 300 |0 (DE-625)143650: |2 rvk | ||
| 100 | 1 | |a Hutter, Marcus |d 1967- |e Verfasser |0 (DE-588)103154576X |4 aut | |
| 245 | 1 | 0 | |a An introduction to universal artificial intelligence |c Marcus Hutter, David Quarel, Elliot Catt |
| 250 | |a First edition | ||
| 264 | 1 | |a Boca Raton ; London ; New York |b CRC Press |c 2024 | |
| 300 | |a xix, 496 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Chapman & Hall/CRC artificial intelligence and robotics series | |
| 520 | 3 | |a "An Introduction to Universal Artificial Intelligence provides a gentle introduction to Universal Artificial Intelligence (UAI), a theory that provides a formal underpinning of what it means for an agent to act intelligently in a general class of environments. First presented in Universal Artificial Intelligence (Hutter, 2004), UAI presents a model in which most other problems in AI can be presented, and unifies ideas from sequential decision theory, Bayesian inference and information theory to construct AIXI, an optimal reinforcement learning agent that learns to act optimally in unknown environments. AIXI represents a theoretical bound on intelligent behaviour, and so we also discuss tractable approximations of this optimal agent. The book covers important practical approaches including efficient Bayesian updating with context tree weighting, and stochastic planning, approximated by sampling with Monte Carlo tree search. Algorithms are also included for the reader to implement, along with experimental results to compare against. This serves to approximate AIXI, as well as being used in state-of-the-art approaches in AI today. The book ends with a philosophical discussion of AGI covering the following key questions: Should intelligent agents be constructed at all, is it inevitable that they will be constructed, and is it dangerous to do so? This text is suitable for late undergraduates and includes an extensive background chapter to fill in the assumed mathematical background"-- | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Bayesian statistical decision theory | |
| 650 | 4 | |a Probabilities | |
| 650 | 4 | |a Algorithms | |
| 650 | 0 | 7 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Überwachtes Lernen |0 (DE-588)4580264-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Wahrscheinlichkeit |0 (DE-588)4137007-7 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Operante Konditionierung |0 (DE-588)4172613-3 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Agent |g Informatik |0 (DE-588)4455835-1 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Sequentialanalyse |0 (DE-588)4128461-6 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Entscheidungstheorie |0 (DE-588)4138606-1 |2 gnd |9 rswk-swf |
| 653 | 0 | |a Intelligence artificielle | |
| 653 | 0 | |a Théorie de la décision bayésienne | |
| 653 | 0 | |a Probabilités | |
| 653 | 0 | |a Algorithmes | |
| 653 | 0 | |a COMPUTERS / Neural Networks | |
| 653 | 0 | |a COMPUTERS / Computer Science | |
| 653 | 0 | |a COMPUTERS / General | |
| 655 | 7 | |0 (DE-588)4151278-9 |a Einführung |2 gnd-content | |
| 689 | 0 | 0 | |a Agent |g Informatik |0 (DE-588)4455835-1 |D s |
| 689 | 0 | 1 | |a Operante Konditionierung |0 (DE-588)4172613-3 |D s |
| 689 | 0 | 2 | |a Überwachtes Lernen |0 (DE-588)4580264-6 |D s |
| 689 | 0 | 3 | |a Entscheidungstheorie |0 (DE-588)4138606-1 |D s |
| 689 | 0 | 4 | |a Sequentialanalyse |0 (DE-588)4128461-6 |D s |
| 689 | 0 | 5 | |a Wahrscheinlichkeit |0 (DE-588)4137007-7 |D s |
| 689 | 0 | |5 DE-604 | |
| 689 | 1 | 0 | |a Künstliche Intelligenz |0 (DE-588)4033447-8 |D s |
| 689 | 1 | |5 DE-604 | |
| 700 | 1 | |a Quarel, David |e Verfasser |4 aut | |
| 700 | 1 | |a Catt, Elliot |e Verfasser |4 aut | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-1-003-46029-9 |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-035094978 | |
Datensatz im Suchindex
| _version_ | 1811856364128960512 |
|---|---|
| adam_text | |
| any_adam_object | |
| author | Hutter, Marcus 1967- Quarel, David Catt, Elliot |
| author_GND | (DE-588)103154576X |
| author_facet | Hutter, Marcus 1967- Quarel, David Catt, Elliot |
| author_role | aut aut aut |
| author_sort | Hutter, Marcus 1967- |
| author_variant | m h mh d q dq e c ec |
| building | Verbundindex |
| bvnumber | BV049753388 |
| classification_rvk | ST 300 |
| ctrlnum | (OCoLC)1424992374 (DE-599)BVBBV049753388 |
| discipline | Informatik |
| edition | First edition |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 c 4500</leader><controlfield tag="001">BV049753388</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20240828</controlfield><controlfield tag="007">t</controlfield><controlfield tag="008">240624s2024 a||| |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781032607153</subfield><subfield code="c">hbk</subfield><subfield code="9">978-1-032-60715-3</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781032607023</subfield><subfield code="c">pbk</subfield><subfield code="9">978-1-032-60702-3</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1424992374</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV049753388</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-29T</subfield><subfield code="a">DE-188</subfield><subfield code="a">DE-522</subfield><subfield code="a">DE-83</subfield><subfield code="a">DE-862</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">ST 300</subfield><subfield code="0">(DE-625)143650:</subfield><subfield code="2">rvk</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hutter, Marcus</subfield><subfield code="d">1967-</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)103154576X</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">An introduction to universal artificial intelligence</subfield><subfield code="c">Marcus Hutter, David Quarel, Elliot Catt</subfield></datafield><datafield tag="250" ind1=" " ind2=" "><subfield code="a">First edition</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Boca Raton ; London ; New York</subfield><subfield code="b">CRC Press</subfield><subfield code="c">2024</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">xix, 496 Seiten</subfield><subfield code="b">Illustrationen, Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Chapman & Hall/CRC artificial intelligence and robotics series</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">"An Introduction to Universal Artificial Intelligence provides a gentle introduction to Universal Artificial Intelligence (UAI), a theory that provides a formal underpinning of what it means for an agent to act intelligently in a general class of environments. First presented in Universal Artificial Intelligence (Hutter, 2004), UAI presents a model in which most other problems in AI can be presented, and unifies ideas from sequential decision theory, Bayesian inference and information theory to construct AIXI, an optimal reinforcement learning agent that learns to act optimally in unknown environments. AIXI represents a theoretical bound on intelligent behaviour, and so we also discuss tractable approximations of this optimal agent. The book covers important practical approaches including efficient Bayesian updating with context tree weighting, and stochastic planning, approximated by sampling with Monte Carlo tree search. Algorithms are also included for the reader to implement, along with experimental results to compare against. This serves to approximate AIXI, as well as being used in state-of-the-art approaches in AI today. The book ends with a philosophical discussion of AGI covering the following key questions: Should intelligent agents be constructed at all, is it inevitable that they will be constructed, and is it dangerous to do so? This text is suitable for late undergraduates and includes an extensive background chapter to fill in the assumed mathematical background"--</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Bayesian statistical decision theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Probabilities</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Algorithms</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Künstliche Intelligenz</subfield><subfield code="0">(DE-588)4033447-8</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Überwachtes Lernen</subfield><subfield code="0">(DE-588)4580264-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Wahrscheinlichkeit</subfield><subfield code="0">(DE-588)4137007-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Operante Konditionierung</subfield><subfield code="0">(DE-588)4172613-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Agent</subfield><subfield code="g">Informatik</subfield><subfield code="0">(DE-588)4455835-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Sequentialanalyse</subfield><subfield code="0">(DE-588)4128461-6</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Entscheidungstheorie</subfield><subfield code="0">(DE-588)4138606-1</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Intelligence artificielle</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Théorie de la décision bayésienne</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Probabilités</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Algorithmes</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">COMPUTERS / Neural Networks</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">COMPUTERS / Computer Science</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">COMPUTERS / General</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="0">(DE-588)4151278-9</subfield><subfield code="a">Einführung</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Agent</subfield><subfield code="g">Informatik</subfield><subfield code="0">(DE-588)4455835-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Operante Konditionierung</subfield><subfield code="0">(DE-588)4172613-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Überwachtes Lernen</subfield><subfield code="0">(DE-588)4580264-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Entscheidungstheorie</subfield><subfield code="0">(DE-588)4138606-1</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="4"><subfield code="a">Sequentialanalyse</subfield><subfield code="0">(DE-588)4128461-6</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="5"><subfield code="a">Wahrscheinlichkeit</subfield><subfield code="0">(DE-588)4137007-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="1" ind2="0"><subfield code="a">Künstliche Intelligenz</subfield><subfield code="0">(DE-588)4033447-8</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="5">DE-604</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Quarel, David</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Catt, Elliot</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Online-Ausgabe</subfield><subfield code="z">978-1-003-46029-9</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-035094978</subfield></datafield></record></collection> |
| genre | (DE-588)4151278-9 Einführung gnd-content |
| genre_facet | Einführung |
| id | DE-604.BV049753388 |
| illustrated | Illustrated |
| indexdate | 2024-10-03T04:01:19Z |
| institution | BVB |
| isbn | 9781032607153 9781032607023 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035094978 |
| oclc_num | 1424992374 |
| open_access_boolean | |
| owner | DE-29T DE-188 DE-522 DE-83 DE-862 DE-BY-FWS |
| owner_facet | DE-29T DE-188 DE-522 DE-83 DE-862 DE-BY-FWS |
| physical | xix, 496 Seiten Illustrationen, Diagramme |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | CRC Press |
| record_format | marc |
| series2 | Chapman & Hall/CRC artificial intelligence and robotics series |
| spellingShingle | Hutter, Marcus 1967- Quarel, David Catt, Elliot An introduction to universal artificial intelligence Artificial intelligence Bayesian statistical decision theory Probabilities Algorithms Künstliche Intelligenz (DE-588)4033447-8 gnd Überwachtes Lernen (DE-588)4580264-6 gnd Wahrscheinlichkeit (DE-588)4137007-7 gnd Operante Konditionierung (DE-588)4172613-3 gnd Agent Informatik (DE-588)4455835-1 gnd Sequentialanalyse (DE-588)4128461-6 gnd Entscheidungstheorie (DE-588)4138606-1 gnd |
| subject_GND | (DE-588)4033447-8 (DE-588)4580264-6 (DE-588)4137007-7 (DE-588)4172613-3 (DE-588)4455835-1 (DE-588)4128461-6 (DE-588)4138606-1 (DE-588)4151278-9 |
| title | An introduction to universal artificial intelligence |
| title_auth | An introduction to universal artificial intelligence |
| title_exact_search | An introduction to universal artificial intelligence |
| title_full | An introduction to universal artificial intelligence Marcus Hutter, David Quarel, Elliot Catt |
| title_fullStr | An introduction to universal artificial intelligence Marcus Hutter, David Quarel, Elliot Catt |
| title_full_unstemmed | An introduction to universal artificial intelligence Marcus Hutter, David Quarel, Elliot Catt |
| title_short | An introduction to universal artificial intelligence |
| title_sort | an introduction to universal artificial intelligence |
| topic | Artificial intelligence Bayesian statistical decision theory Probabilities Algorithms Künstliche Intelligenz (DE-588)4033447-8 gnd Überwachtes Lernen (DE-588)4580264-6 gnd Wahrscheinlichkeit (DE-588)4137007-7 gnd Operante Konditionierung (DE-588)4172613-3 gnd Agent Informatik (DE-588)4455835-1 gnd Sequentialanalyse (DE-588)4128461-6 gnd Entscheidungstheorie (DE-588)4138606-1 gnd |
| topic_facet | Artificial intelligence Bayesian statistical decision theory Probabilities Algorithms Künstliche Intelligenz Überwachtes Lernen Wahrscheinlichkeit Operante Konditionierung Agent Informatik Sequentialanalyse Entscheidungstheorie Einführung |
| work_keys_str_mv | AT huttermarcus anintroductiontouniversalartificialintelligence AT quareldavid anintroductiontouniversalartificialintelligence AT cattelliot anintroductiontouniversalartificialintelligence |