Download Agent-Based Approaches in Economic and Social Complex by Aki-Hiro Sato (auth.), Shu-Heng Chen, Takao Terano, Ryuichi PDF

By Aki-Hiro Sato (auth.), Shu-Heng Chen, Takao Terano, Ryuichi Yamamoto (eds.)

Agent-based modeling/simulation is an emergent method of the research of social and monetary platforms. It presents a bottom-up experimental strategy to be utilized to social sciences akin to economics, administration, sociology, and politics in addition to a few engineering fields facing social actions. This ebook contains chosen papers awarded on the 6th foreign Workshop on Agent-Based techniques in financial and Social advanced structures held in Taipei in 2009. we have now 39 shows within the convention, and 14 papers are chosen to be integrated during this quantity. those 14 papers are then grouped into six elements: Agent-based monetary markets; monetary forecasting and funding; Cognitive modeling of brokers; Complexity and coverage research; Agent-based modeling of fine societies; and Miscellany. The learn offered the following indicates the cutting-edge during this speedily turning out to be field.

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Extra resources for Agent-Based Approaches in Economic and Social Complex Systems VI: Post-Proceedings of The AESCS International Workshop 2009

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Actually, the importance of this research trend that takes the behavioral characteristics into account has been noticed. As mentioned in [10]: Finally, given the demonstrated ingenuity of the theory branch of finance, and given the long litany of apparent judgment biases unearthed by cognitive psychologists ([5]), it is safe to predict that we will soon see a menu of behavioral models that can be mixed and matched to explain specific anomalies. (p. 291) DeBondt and Thaler [5] state that perhaps the most robust finding in the psychology of judgment is that people are overconfident.

N (1) where lb and ub indicate the lower and upper bounds for each parameter, this allows each parameter β j to be transformed by function L(x) to be an integer y j satisfying its boundaries, which can be encoded as n∗ D bits of binary code. y j = L(x j ), c j = u1j u2j . . uDj j , j = 1 . . D, uDj ∈ {0, 1} (2) A chromosome is defined as a binary string combining binary codes of all parameters. Specifically, there are 27∗ D bits in a chromosome. 2. 5. The mutation and cross-over operations occur in random order.

Natarajan et al. [6] utilized PSO and BPN to train a neural network, and compared PSO with BPN. The results showed that PSO outperforms BPN. A model proposed by Geethanjali et al. [7] monitors and discriminates among the different operating conditions of power transformers. The PSO technique is used to train the multi-layered feed forward neural networks to discriminate among different operating conditions. These two ANNs were trained using back propagation neural network algorithm (BPN) and the PSO technique; next, the simulated results were compared.

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