For more theory and computation of Dynamic Squared Models, please refer to jupyter notebook "dynamic programming squared model.ipynb". For full mathematical analysis, please refer to pdf titled ...

Sequence alignment methods often use something called a 'dynamic programming' algorithm. What is dynamic programming and how does it work?

This paper introduces a sensor-based approach for finding an optimized solution for online coverage path planning problem. Compared to traditional approaches we can augment. Multi-objective ...

In this work, a novel value function-based reinforcement learning (RL) approach, descending dynamic policy programming (DDPP) is proposed to address the issues of sample-efficiency and learning ...

Learn what dynamic programming and greedy algorithms are, how they differ, and when to use them. See examples of problems and code solutions.

Discover the connection between maximum principle and dynamic programming in stochastic games. Explore the relationships between adjoint processes, Hamiltonian function, and value function. Explore ...