Read e-book online AI 2013: Advances in Artificial Intelligence: 26th PDF

By Xiaoxin Jing, Dongmo Zhang, Xudong Luo (auth.), Stephen Cranefield, Abhaya Nayak (eds.)

ISBN-10: 3319036793

ISBN-13: 9783319036793

ISBN-10: 3319036807

ISBN-13: 9783319036809

This ebook constitutes the refereed court cases of the twenty sixth Australasian Joint convention on man made Intelligence, AI 2013, held in Dunedin, New Zealand, in December 2013. The 35 revised complete papers and 19 revised brief papers awarded have been rigorously reviewed and chosen from a hundred and twenty submissions. The papers are geared up in topical sections as brokers; AI purposes; cognitive modelling; laptop imaginative and prescient; constraint pride, seek and optimisation; evolutionary computation; online game enjoying; wisdom illustration and reasoning; computing device studying and knowledge mining; ordinary language processing and data retrieval; making plans and scheduling.

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Read or Download AI 2013: Advances in Artificial Intelligence: 26th Australasian Joint Conference, Dunedin, New Zealand, December 1-6, 2013. Proceedings PDF

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Get AI 2013: Advances in Artificial Intelligence: 26th PDF

This publication constitutes the refereed court cases of the twenty sixth Australasian Joint convention on man made Intelligence, AI 2013, held in Dunedin, New Zealand, in December 2013. The 35 revised complete papers and 19 revised brief papers offered have been conscientiously reviewed and chosen from one hundred twenty submissions. The papers are geared up in topical sections as brokers; AI functions; cognitive modelling; computing device imaginative and prescient; constraint delight, seek and optimisation; evolutionary computation; video game taking part in; wisdom illustration and reasoning; computing device studying and knowledge mining; average language processing and knowledge retrieval; making plans and scheduling.

Additional resources for AI 2013: Advances in Artificial Intelligence: 26th Australasian Joint Conference, Dunedin, New Zealand, December 1-6, 2013. Proceedings

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26–31, 2013. c Springer International Publishing Switzerland 2013 A Mechanism to Improve Efficiency for Negotiations 27 Upon observing the action by the agent with private information, other agents can decide their own best course of actions. , time delays when there are discount factors) [4, 5], transaction costs [6], or bargaining deadlines [7, 8]. Our approach, on the other hand, applies a mechanism of biased distribution of the observable gains from trade to encourage the parties with private information to truthfully reveal their types.

Inefficiencies are a consequence of the incentives to misrepresent a bargainers’ valuations between those with private information. The mechanism propose in this paper aims to remove such incentives by devising ways to distribute the resulting gains from trade in such a way that the bargainer who can still make a concession becomes more willing to actually make that concession. 1 1 The “type” of a player embodies any private information that is relevant to the player’s decision making. S. Cranefield and A.

219, pp. 1–34. Springer, Heidelberg (2008) 11. : Decision analysis using belief functions. International Journal of Approximate Reasoning 4(5), 391–417 (1990) 12. : A model for decision making with missing, imprecise, and uncertain evaluations of multiple criteria. International Journal of Intelligent Systems 28(2), 152–184 (2013) 13. : Games with ambiguous payoffs and played by ambiguity and regret minimising players. , Zhang, D. ) AI 2012. LNCS, vol. 7691, pp. 409–420. Springer, Heidelberg (2012) 14.

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AI 2013: Advances in Artificial Intelligence: 26th Australasian Joint Conference, Dunedin, New Zealand, December 1-6, 2013. Proceedings by Xiaoxin Jing, Dongmo Zhang, Xudong Luo (auth.), Stephen Cranefield, Abhaya Nayak (eds.)


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