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Simple Heuristics That Make Us Smart
Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional
Designing Neural Networks using Genetic Algorithms
TLDR
This semester, the RoboCup Keepaway Machine Learning testbed provided an excellent environment to train the authors' agents, but still needed to scale down the problem in order to do a feasibility study.
Can There Ever Be Too Many Options? A Meta-Analytic Review of Choice Overload
The choice overload hypothesis states that an increase in the number of options to choose from may lead to adverse consequences such as a decrease in the motivation to choose or the satisfaction with
Optimal foraging in semantic memory.
TLDR
Evidence for local structure in memory search and patch depletion preceding dynamic local-to-global transitions between patches is found, and dynamic models significantly outperformed nondynamic models.
Précis of Simple heuristics that make us smart
TLDR
It is shown how simple building blocks that control information search, stop search, and make decisions can be put together to form classes of heuristics, including: ignorance-based and one-reason decision making for choice, elimination models for categorization, and satisficing heuristic for sequential search.
Mate choice turns cognitive
Ecological Rationality: Intelligence in the World
"More information is always better, and full information is best. More computation is always better, and optimization is best." More-is-better ideals such as these have long shaped our vision of
A Connectionist Approach To Algorithmic Composition
TLDR
This paper presents a particular type of PDP network for music composition applications and provides an indication of the power and range of P DP methods for algorithmic composition and to encourage others to begin exploring this new approach.
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