Systems whose information processing structures are fully programmed are difficult to design for all but the simplest applications. Real-world environments call for systems that are able to modify their behavior by changing their information processing structures. Cognitive and information structures and processes, embodied in living systems, display many effective designs for biological intelligent agents. They are also a source of ideas for designing artificial intelligent agents. This book explores a central issue in artificial intelligence, cognitive science, and artificial life: how to design information structures and processes that create and adapt intelligent agents through evolution and learning.
The book is organized around four topics: the power of evolution to determine effective solutions to complex tasks, mechanisms to make evolutionary design scalable, the use of evolutionary search in conjunction with local learning algorithms, and the extension of evolutionary search in novel directions.
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