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This work can be seen as a starting step toward modeling the learning of human language in the LIDA cognitive architecture.
The chapter concludes that, as modeling the learning and behavior of traders improves, and as the software and hardware available for modeling and analysis improves, the techniques will provide ever greater insights into improving the designs of existing markets, and facilitating the design of new markets.
The cusum method [24], despite its wide use, is problematic for modeling the learning curve.
We have applied temporal averaging methods on slow/fast systems modeling the learning mechanisms occurring in linear stochastic neural networks.
However, currently there is no universally accepted method for modeling the learning curve (see [22, 23] for systematic reviews).
Statistical methods for modeling the learning curve ideally should aim to estimate three parameters: rate of learning, baseline (starting) skill level and final skill level (asymptote) [23].
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How can we model the learning of lexical propensities together with a frequency-matching grammar?
A cognitive model using Adaptive Control of Thought-Rational (ACT-R) was built to model the learning process of lateral control skills.
The current study examined a computational method using a cognitive architecture to model the learning process of vehicle lateral control.
Intelligence on modeling the relationships of learning goals, learning outcomes and learning activities is then required.
In the model, the learning weights are adjusted by the proposed anxious confident decayed brain emotional learning rules (ACDBEL).
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