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Under adaptive learning, recursive algorithms are proposed to represent how agents update their beliefs over time. For … consistent with the statistical properties of the learning algorithm. Our method is generically formulated to cover different … specifications of the learning mechanism, such as the Least Squares and the Stochastic Gradient algorithms. Using simulations we show …
Persistent link: https://www.econbiz.de/10011619472
Problem definition: Intraproject learning in project scheduling is concerned with the use of learning among the similar … tasks in the project to improve the overall performance of the project schedule. Under intraproject learning, knowledge …. We provide the first model and solution algorithms to tackle this intraproject learning problem.Methodology/results: We …
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We construct the first algorithm for the perfect foresight solution of otherwise linear models with occasionally binding constraints, with fixed terminal conditions, that is guaranteed to return a solution in finite time, if one exists. We also provide a proof of the inescapability of the "curse...
Persistent link: https://www.econbiz.de/10011518454
We present the first necessary and sufficient conditions for there to be a unique perfect-foresight solution to an otherwise linear dynamic model with occasionally binding constraints, given a fixed terminal condition. We derive further conditions on the existence of a solution in such models....
Persistent link: https://www.econbiz.de/10011518459
We present the first necessary and sufficient conditions for there to be a unique perfect-foresight solution to an otherwise linear dynamic model with occasionally binding constraints, given a fixed terminal condition. We derive further results on the existence of a solution in the presence of...
Persistent link: https://www.econbiz.de/10011717372
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