AI 2004: Advances in Artificial Intelligence: 17th by Seung-Ryong Yang, Jun-Ki Min, Sung-Bae Cho (auth.), Geoffrey

By Seung-Ryong Yang, Jun-Ki Min, Sung-Bae Cho (auth.), Geoffrey I. Webb, Xinghuo Yu (eds.)

This e-book constitutes the refereed complaints of the seventeenth Australian convention on man made Intelligence, AI 2004, held in Cairns, Australia, in December 2004.

The seventy eight revised complete papers and sixty two revised brief papers offered have been conscientiously reviewed and chosen from 340 submissions. The papers are equipped in topical sections on brokers; biomedical functions; machine imaginative and prescient, picture processing, and development reputation; ontologies, wisdom discovery and information mining; ordinary language and speech processing; challenge fixing and reasoning; robotics; and gentle computing.

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Extra info for AI 2004: Advances in Artificial Intelligence: 17th Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 4-6, 2004. Proceedings

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On the other hand, emergence can offer a much richer solution space and lead to better solutions if the unpredictability can be controlled. Biological evolution offers many examples where this has been used to advantage [4]. A traditional approach to the design of complex systems is hierarchical decomposition [5], where the problem is broken down into a (sometimes large) number of layers which are more amenable to solution. Unfortunately this process, whilst often allowing a design to be achieved almost always suppresses emergent behaviour, thus denying the designer access to the rich solution space which complexity can provide.

Variation of average payoffs in a balanced job concentration. Notice Y axis value between two figures. Employers get more payoffs relatively when a coalition is not allowed (dashed lines in Fig. 3(a)). 3 Low Job Concentration In this section, we analyze the behavioral patterns of the agents when a job concentration is low (JCON=1/2) which means the number of employers is two times more than the number of workers (NW/NE=1/2). In this environment, workers have an advantage in finding his worksite partner.

V is updated based on the values of the parameters P, D, gpr, or r and their associated weights. For example, if P is “UP”, vU is updated by adding the weight of P, wP: vU = vU + wP. This process is carried out for all parameters. 3. Finally, the report direction g corresponds to the maximum element of v. A benchmark report-direction function GB1 was also used to test the efficacy of G. This is simply defined g = r, representing a fully random report direction. 3 The Portal-Derived Functions GP and GPV The general form of the portal-derived function is similar to that for G, except that the pheremone value VP needs to be considered.

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