Similar Search Results

Catastrophic thresholds, Bayesian learning and the robustness of climate policy recommendations

Chang, Wonjun; Rutherford, Thomas F. - In: Climate change economics 8 (2017) 4, pp. 1-23

Persistent link: https://www.econbiz.de/10011857264

Decision making in the emissions-market under uncertainty

Spangardt, Gorden; Lucht, Michael; Wolf, Christian; … - In: Emissions trading and business : with 52 tables ; …, (pp. 119-132). 2006

Persistent link: https://www.econbiz.de/10003385488

Impacts of uncertainty and increasing returns on sustainable energy development and climate change : a stochastic optimization approach

Gritsevskyi, A.; Rogner, Hans-Holger - In: Coping with uncertainty : modeling and policy issues, (pp. 195-216). 2006

Persistent link: https://www.econbiz.de/10003394850

A two-stage stochastic optimization planning framework to decarbonize deeply electric power systems

Boffino, Luigi; Conejo, Antonio J.; Sioshansi, Ramteen; … - In: Energy economics 84 (2019), pp. 1-19

Persistent link: https://www.econbiz.de/10012183445

On boundedness of Q-learning iterates for stochastic shortest path problems

Yu, Huizhen; Bertsekas, Dimitri P. - In: Mathematics of operations research 38 (2013) 2, pp. 209-227

Persistent link: https://www.econbiz.de/10009751534

Stochastic Gradient Versus Recursive Least Squares Learning

Slobodyan, Sergey - 2008

In this paper, we perform an in - depth investigation of relative merits of two adaptive learning algorithms with constant gain, Recursive Least Squares (RLS) and Stochastic Gradient (SG), using the Phelps model of monetary policy as a testing ground. The behavior of the two learning algorithms...

Persistent link: https://www.econbiz.de/10012724434