What is dynamic programming?

By Sean R. Eddy. 2004

2,378 citations recorded by the source corpus.

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In Molecular Biology

Citations in the corpus

Dynamic Programming (2018, neutral): “The paradigm was introduced by the mathematician Richard Bellman in the 1940s and applied in control theory [1].”
Modeling and Control of a Power-Split Hybrid Vehicle (2008, background): “previous sections, performance benchmarks will be obtained from the dynamic programming (DP) [24] technique.”
The Dawning of a New Era in Applied Mathematics (2021, background): “To begin with, it is interesting to note that the term “curse of dimensionality” was first coined by Richard Bellman in the context of dynamic programming [1].”
Reinforcement Learning: A Novel Method for Optimal Control of Propofol-Induced Hypnosis (2011, methodology): “If these probabilities are available, an optimal control policy may be determined using the well-studied method of dynamic programming.(20) RL presents one means of empirically determining those state transition probabilities to optimally control a patient’s state.”
Reinforcement learning for factored Markov decision processes (2002, methodology): “The Markov assumption underlies a large proportion of control theory, machine learning and signal processing including Kalman filters [Kalman 1960], hidden Markov models (HMMs) [Rabiner and Juang 1986], two-time-slice dynamic Bayesian networks [Dean and Kanazawa 1989], dynamic programming (DP) [Bell”
Teamwork in Self-Organized Robot Colonies (2009, methodology): “O’Hara and Balch [62], for instance, use a sensor network with up to 156 sensor nodes that compute the shortest path using the distributed Bellman–Ford algorithm [12], and test the impact of different configurations of sensor placement.”
Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems (2017, methodology): “When the reward function and the state transition model are known it can be done by means of the Bellman optimality equation (Bellman 1957).”
Iterative Linearization Scheme for Convex Nonlinear Equations: Application to Optimal Operation of Water Distribution Systems (2013, methodology): “Sterling and Coulbeck (1975) used a dynamic modeling approach to minimize the costs of pump operation of a simple water supply system.”
Estimation of Optimal Dynamic Treatment Regimes (2014, neutral): “From dynamic programming [43], it follows that”
Next-Generation Airborne Collision Avoidance System (2012, background): “Markov decision processes (MDP) are a general framework for formulating sequential decision problems [9].”
Cooperative Co-Evolution With Differential Grouping for Large Scale Optimization (2014, background): “This is referred to as “the curse o f dimensionality” [9].”
Optimal Play of the Dice Game Pig (2004, background): “Value iteration [Bellman 1957; Bertsekas 1987; Sutton and Barto 1998] is a process that iteratively improves estimates of the value of being in each state until the estimates are “good enough.””