000753469 000__ 03206cam\a2200469Ii\4500
000753469 001__ 753469
000753469 005__ 20230306141559.0
000753469 006__ m\\\\\o\\d\\\\\\\\
000753469 007__ cr\cn\nnnunnun
000753469 008__ 160126s2016\\\\sz\a\\\\ob\\\\000\0\eng\d
000753469 019__ $$a936882235
000753469 020__ $$a9783319282435$$q(electronic book)
000753469 020__ $$a3319282433$$q(electronic book)
000753469 020__ $$z9783319282428
000753469 0247_ $$a10.1007/978-3-319-28243-5$$2doi
000753469 035__ $$aSP(OCoLC)ocn936040188
000753469 035__ $$aSP(OCoLC)936040188$$z(OCoLC)936882235
000753469 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dYDXCP$$dIDEBK$$dGW5XE$$dN$T$$dAZU$$dCDX$$dCOO$$dOCLCF$$dEBLCP$$dOCLCQ
000753469 049__ $$aISEA
000753469 050_4 $$aQA76.76.I58
000753469 08204 $$a006.3$$223
000753469 1001_ $$aBaarslag, Tim,$$eauthor.
000753469 24510 $$aExploring the strategy space of negotiating agents$$h[electronic resource] :$$ba framework for bidding, learning and accepting in automated negotiation /$$cTim Baarslag.
000753469 264_1 $$aSwitzerland :$$bSpringer,$$c2016.
000753469 300__ $$a1 online resource (xxi, 276 pages) :$$billustrations.
000753469 336__ $$atext$$btxt$$2rdacontent
000753469 337__ $$acomputer$$bc$$2rdamedia
000753469 338__ $$aonline resource$$bcr$$2rdacarrier
000753469 4901_ $$aSpringer theses,$$x2190-5061
000753469 500__ $$a"Nominated as an outstanding PhD thesis by Delft University of Technology, The Netherlands."
000753469 504__ $$aIncludes bibliographical references.
000753469 5050_ $$aIntroduction -- Background -- A Component-based Architecture to Explore the Space of Negotiation Strategies -- Effective Acceptance Conditions -- Accepting Optimally with Incomplete Information -- Measuring the Performance of Online Opponent Models -- Predicting the Performance of Opponent Models -- A Quantitative Concession-Based Classification Method of Bidding Strategies -- Optimal Non-adaptive Concession Strategies -- Putting the Pieces Together -- Conclusion.
000753469 506__ $$aAccess limited to authorized users.
000753469 520__ $$aThis book reports on an outstanding thesis that has significantly advanced the state-of-the-art in the area of automated negotiation. It gives new practical and theoretical insights into the design and evaluation of automated negotiators. It describes an innovative negotiating agent framework that enables systematic exploration of the space of possible negotiation strategies by recombining different agent components. Using this framework, new and effective ways are formulated for an agent to learn, bid, and accept during a negotiation. The findings have been evaluated in four annual instantiations of the International Automated Negotiating Agents Competition (ANAC), the results of which are also outlined here. The book also describes several methodologies for evaluating and comparing negotiation strategies and components, with a special emphasis on performance and accuracy measures.
000753469 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 29, 2016).
000753469 650_0 $$aIntelligent agents (Computer software)
000753469 77608 $$iPrint version:$$z9783319282428
000753469 830_0 $$aSpringer theses.
000753469 852__ $$bebk
000753469 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-28243-5$$zOnline Access$$91397441.1
000753469 909CO $$ooai:library.usi.edu:753469$$pGLOBAL_SET
000753469 980__ $$aEBOOK
000753469 980__ $$aBIB
000753469 982__ $$aEbook
000753469 983__ $$aOnline
000753469 994__ $$a92$$bISE