Computational Cognitive Science.pdf
Human learning and reasoning is founded on multiple knowledge representations with different kinds of structures, such as trees, chains, dominance hierarchies, neighborhood graphs, and directed networks. This class uses probabilistic inference methods from machine learning and Bayesian statistics, operating over different kinds of structured representational systems, to explain how people’s domain knowledge can support a wide range of learning and reasoning tasks, and how these knowledge structures may themselves be learned from experience.
An Introduction to Intelligent and Autonomous Control.pdf
An introduction to the field of intelligent control with a broad treatment of topics by several authors (including hierarchical/ distributed intelligent control, fuzzy control, expert control, neural networks, planning systems, and applications).
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