An Introduction to Dynamic Optimization and Optimal Control: Models, Solutions, and Approximations Duration: 20 hours Teachers: Giorgio Gnecco - IMT - Institute for Advanced Studies, Lucca (Italy) - giorgio.gnecco@imtluc

Source URL: phd.dibris.unige.it

• Mathematical optimization
• Equations
• Operations research
• Optimal control
• Dynamic programming
• Bellman equation
• Lev Pontryagin
• Kalman filter
• Algebraic Riccati equation
• Stochastic programming
• Dimitri Bertsekas

Inverse Reinforcement Learning through Structured Classification Edouard Klein1,2 LORIA – team ABC Nancy, France

Source URL: www.ilhaire.eu

• Statistical classification
• Dynamic programming
• Stochastic control
• Computational neuroscience
• Reinforcement learning
• Loss function
• Markov decision process
• Artificial neural network
• Support vector machine
• Expected value
• Valuation
• Stochastic programming

Journal of EconomicsDOIs00712Journal of Economics Printed in Austria

Source URL: www.waelde.com

• Dynamic programming
• Stochastic calculus
• Equations
• Stochastic processes
• HamiltonJacobiBellman equation
• Optimal control
• Stochastic differential equation
• Thorn
• Bellman equation

330 IEEE TRANSACTIONS ON AUTONOMOUS MENTAL DEVELOPMENT, VOL. 4, NO. 4, DECEMBER 2012 Model-Free Reinforcement Learning of Impedance Control in Stochastic Environments

Source URL: www-clmc.usc.edu

Gaussian Belief Space Planning for Imprecise Articulated Robots Alex Lee Sachin Patil John Schulman Zoe McCarthy Jur van den Berg Ken Goldberg Pieter Abbeel Abstract— For many emerging applications, actuators are being

Source URL: goldberg.berkeley.edu

• Statistics
• Mathematical analysis
• Probability
• Robot control
• Mathematical optimization
• Dynamic programming
• Stochastic control
• Partially observable Markov decision process
• Trajectory optimization
• Kalman filter
• Motion planning
• Normal distribution

A L IST OF M ODELS AVAILABLE IN THE M ACROECONOMIC M ODEL DATA BASE ( VERSION 2.0, 61 MODELSS MALL C ALIBRATED M ODELS (14 MODELS )

Source URL: www.macromodelbase.com

• Economics
• Macroeconomics
• Economy
• New Keynesian economics
• Dynamic stochastic general equilibrium
• Macroeconomic model
• Inflation targeting
• Journal of Economic Dynamics and Control
• Nominal rigidity

Technical efficiency effects of input controls: evidence from Australia’s banana prawn fishery Tom Kompas, Tuong Nhu Che and R. Quentin Grafton Australian National University

Source URL: een.anu.edu.au

• Caridea
• Stochastic frontier analysis
• Indian prawn
• Shrimp fishery
• Control theory

Using Social Networks to Aid Homeless Shelters: Dynamic Influence Maximization under Uncertainty Amulya Yadav, Hau Chan1 , Albert Jiang1 , Haifeng Xu, Eric Rice, Milind Tambe University of Southern California, Los Angele

Source URL: teamcore.usc.edu

• Networks
• Graph theory
• Network theory
• Dynamic programming
• Partially observable Markov decision process
• Stochastic control
• Centrality
• Social network analysis
• Tree
• Flow network

MITSUBISHI ELECTRIC RESEARCH LABORATORIES http://www.merl.com Truncated Approximate Dynamic Programming with Task-Dependent Terminal Value Farahmand, A.-M.; Nikovski, D.N.; Igarashi, Y.; Konaka, H.

Source URL: www.merl.com

• Mathematical optimization
• Operations research
• Dynamic programming
• Markov processes
• Stochastic control
• Markov decision process
• Reinforcement learning
• Convolution
• Optimal control
• Q-learning

Cognitive Science–618 Copyright © 2014 Cognitive Science Society, Inc. All rights reserved. ISSN: printonline DOI: cogsInferring Learners’ Knowledge From Their Ac

Source URL: cocosci.berkeley.edu

• Dynamic programming
• Markov processes
• Stochastic control
• Cognitive science
• Probability theory
• Markov decision process
• Reinforcement learning
• Theory of mind
• Probability
• Psychology
• Cognition