| 000 | 03508nam a22005775i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-28243-5 | ||
| 003 | DE-He213 | ||
| 005 | 20220801222408.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 160121s2016 sz | s |||| 0|eng d | ||
| 020 |
_a9783319282435 _9978-3-319-28243-5 |
||
| 024 | 7 |
_a10.1007/978-3-319-28243-5 _2doi |
|
| 050 | 4 | _aTJ212-225 | |
| 050 | 4 | _aTJ210.2-211.495 | |
| 072 | 7 |
_aTJFM _2bicssc |
|
| 072 | 7 |
_aTEC037000 _2bisacsh |
|
| 072 | 7 |
_aTJFM _2thema |
|
| 082 | 0 | 4 |
_a629.8 _223 |
| 100 | 1 |
_aBaarslag, Tim. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _961264 |
|
| 245 | 1 | 0 |
_aExploring the Strategy Space of Negotiating Agents _h[electronic resource] : _bA Framework for Bidding, Learning and Accepting in Automated Negotiation / _cby Tim Baarslag. |
| 250 | _a1st ed. 2016. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
|
| 300 |
_aXXI, 276 p. 58 illus., 21 illus. in color. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aSpringer Theses, Recognizing Outstanding Ph.D. Research, _x2190-5061 |
|
| 505 | 0 | _aIntroduction -- Background -- A Component-based Architecture to Explore the Space of Negotiation Strategies -- Effective Acceptance Conditions -- Accepting Optimally with Incomplete Information -- Measuring the Performance of Online Opponent Models -- Predicting the Performance of Opponent Models -- A Quantitative Concession-Based Classification Method of Bidding Strategies -- Optimal Non-adaptive Concession Strategies -- Putting the Pieces Together -- Conclusion. | |
| 520 | _aThis book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the area of automated negotiation. It gives new practical and theoretical insights into the design and evaluation of automated negotiators. It describes an innovative negotiating agent framework that enables systematic exploration of the space of possible negotiation strategies by recombining different agent components. Using this framework, new and effective ways are formulated for an agent to learn, bid, and accept during a negotiation. The findings have been evaluated in four annual instantiations of the International Automated Negotiating Agents Competition (ANAC), the results of which are also outlined here. The book also describes several methodologies for evaluating and comparing negotiation strategies and components, with a special emphasis on performance and accuracy measures. | ||
| 650 | 0 |
_aControl engineering. _931970 |
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| 650 | 0 |
_aRobotics. _92393 |
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| 650 | 0 |
_aAutomation. _92392 |
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| 650 | 0 |
_aArtificial intelligence. _93407 |
|
| 650 | 0 |
_aEconometrics. _920971 |
|
| 650 | 1 | 4 |
_aControl, Robotics, Automation. _931971 |
| 650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
| 650 | 2 | 4 |
_aQuantitative Economics. _931722 |
| 710 | 2 |
_aSpringerLink (Online service) _961265 |
|
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319282428 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319282442 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319803050 |
| 830 | 0 |
_aSpringer Theses, Recognizing Outstanding Ph.D. Research, _x2190-5061 _961266 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-28243-5 |
| 912 | _aZDB-2-ENG | ||
| 912 | _aZDB-2-SXE | ||
| 942 | _cEBK | ||
| 999 |
_c80721 _d80721 |
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