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

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

Fast Algorithms for Online Stochastic Convex Programming Shipra Agrawal∗ Abstract We introduce the online stochastic Convex Programming (CP) problem, a very general version of stochastic online problems which allows ar

Source URL: research.microsoft.com

Weighted SGD for ?𝓅 Regression with Randomized Preconditioning

Source URL: www.stat.berkeley.edu

• Operations research
• Econometrics
• Convex optimization
• Numerical linear algebra
• Estimation theory
• Preconditioner
• Support vector machine
• Linear regression
• Gradient descent
• Regression analysis
• Stochastic gradient descent
• Linear programming

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

Targeting Specific Distributions of Trajectories in MDPs∗ David L. Roberts1 , Mark J. Nelson1 , Charles L. Isbell, Jr.1 , Michael Mateas1 , Michael L. Littman2 1 2

Source URL: www.kmjn.org

• Dynamic programming
• Markov processes
• Stochastic control
• Belief revision
• Reinforcement learning
• Markov decision process
• Probability distribution

Cognitive Science–43 Copyright © 2015 Cognitive Science Society, Inc. All rights reserved. ISSN: printonline DOI: cogsFaster Teaching via POMDP Planning

Source URL: cocosci.berkeley.edu

• Dynamic programming
• Markov processes
• Stochastic control
• Partially observable Markov decision process
• Educational psychology
• Educational technology
• Automated planning and scheduling
• Markov decision process
• Concept learning
• Intelligent tutoring system

The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty Ron Alterovitz Thierry Sim´eon

Source URL: goldberg.berkeley.edu

• Probability theory
• Mathematical analysis
• Mathematics
• Markov processes
• Robot control
• Classical mechanics
• Markov models
• Dynamic programming
• Motion planning
• Stochastic roadmap simulation
• Probabilistic roadmap
• Markov decision process