Download AI 2013: Advances in Artificial Intelligence: 26th by Xiaoxin Jing, Dongmo Zhang, Xudong Luo (auth.), Stephen PDF

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

This publication constitutes the refereed court cases of the twenty sixth Australasian Joint convention on synthetic Intelligence, AI 2013, held in Dunedin, New Zealand, in December 2013. The 35 revised complete papers and 19 revised brief papers awarded have been conscientiously reviewed and chosen from a hundred and twenty submissions. The papers are prepared in topical sections as brokers; AI functions; cognitive modelling; machine imaginative and prescient; constraint delight, seek and optimisation; evolutionary computation; online game taking part in; wisdom illustration and reasoning; computer studying and information mining; ordinary language processing and data retrieval; making plans and scheduling.

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

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AI 2013, LNAI 8272, pp. 14–25, 2013. c Springer International Publishing Switzerland 2013 Security Games with Ambiguous Information about Attacker Types 15 religious-cultural, and single issue terrorist [7]. , kidnapping, bombing, and so on) to attack targets and so gain different payoffs [8]. If the defender just knows they will be attacked by the attacker with several possible types and the probability distribution over these types, we can use Bayesian Stackelberg game models [1–4] to solve the problem.

Chatterjee and Samuelson establish a (unique) Nash equilibrium for their negotiation setting by using time as a strategic variable and imposing costly delays during negotiation. While the use of impatience, via costly delays, as the strategic information device has been a common practice in the literature of bargaining, this is certainly not applicable in every negotiation. Some researchers even claim that in some negotiations some parties may prefer a later agreement to an early one [15]. Also, a necessary consequence of costly delays is that they prevent full efficiency.

However, we have shown that our model can guarantee the safer result than the model based on uniform random probability in ambiguous environment. In the field of games under ambiguity, Eichberger and Kelsey [18] define a notion of equilibrium under ambiguity to explain the hypothesis that the result, from changing an apparently irrelevant parameter, contradicts Nash equilibrium. In their two-person games, they view their opponents’ behavior as ambiguous based on non-additive beliefs. And Marco and Romaniello [19] try to use an ambiguity model to remedy some defects of Nash equilibrium.

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