Controlling Uncertainty: Decision Making and Learning in Complex WorldsControlling Uncertainty: Decision Making and Learning in Complex Worlds reviews and discusses the most current research relating to the ways we can control the uncertain world around us.
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Contents
Control systems engineering | |
Cybernetics artificial intelligence | |
Human factors HCI ergonomics and cognitive | |
Social psychology organizational psychology | |
Cognitive psychology | |
Other editions - View all
Controlling Uncertainty: Decision Making and Learning in Complex Worlds Magda Osman No preview available - 2010 |
Controlling Uncertainty: Decision Making and Learning in Complex Worlds Magda Osman No preview available - 2010 |
Common terms and phrases
achieve actions activity adaptive analysis Artificial Intelligence associated assumptions automated Bandura Bayesian behave brain causal causes chapter cognitive psychology Cognitive Science complex systems components concerning control behaviours control systems engineering control theory control uncertainty cortex cortical cybernetics Dayan decision decision-making described developed discussion dynamic effects estimates evaluate examine example expected feedback formal models function goal goal-directed behaviours human factors human factors research human operator input interaction internal involves issues Journal judgements Kalman filter knowledge learning algorithms levers linear machine learning mechanism monitoring motivation neural networks neuroeconomics Neuroscience occur optimal organizational outcome output people’s perceptual control theory performance predict prefrontal prefrontal cortex Press probabilistic probability problem properties proposed puppet Q-learning reason refers reinforcement learning relation relationship reward self-efficacy sense of agency signal situations social psychology specific strategies studies systems e.g. task types uncertain environment understanding variables Wiener