Learn how to solve the knapsack problem with two common approaches: dynamic programming and greedy methods. Compare their pros and cons and decide which one to use.

The Dynamic Programming implementation should always return the fewest number of coins in order to make change for a given amount. The Greedy algorithm does not if we use the Roman Republic currency, ...

<P>This chapter considers temporal difference algorithms within the context of infinite-horizon finite-state dynamic programming problems with discounted cost and linear cost function approximation.

Notes of Stanford's Algorithm Course from Coursera - algorithm-notes/Course 3 (Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming)/Week1.md at master · the-robot/algorithm-notes ...

<P>This chapter considers temporal difference algorithms within the context of infinite-horizon finite-state dynamic programming problems with discounted cost and linear cost function approximation.