### Table 2: The number of iterations for the algorithms.

"... In PAGE 6: ... For this implementation we selected r to be 4. In Table2 , we tabulate the number of iterations for the algorithms as a function of the matrix size and the number processors. Table 2: The number of iterations for the algorithms.... ..."

### Table 6: The Policy Iteration Algorithm

1997

"... In PAGE 29: ... Note that if we plug f into Equation (3), the new policy is unchanged|it is still the optimal policy. This de nes the algorithm known as policy iteration, shown in Table6 . It is easy to show that policy iteration converges in a xed number of iterations.... ..."

Cited by 172

### Table 6: The Policy Iteration Algorithm

"... In PAGE 20: ... Note that if we plug f into Equation (3), the new policy is unchanged|it is still the optimal policy. This de nes the algorithm known as policy iteration, shown in Table6 . It is easy to show that policy iteration converges in a xed number of iterations.... ..."

### Table 7: The Value Iteration Algorithm

1997

Cited by 172

### Table 2: The policy iteration algorithm

"... In PAGE 18: ... The policy is initially chosen at random, and the process terminates when no improvement can be found. The algorithm is shown in Table2 . This process converges to an optimal policy (Puterman 1994).... In PAGE 20: ... The representation of the policy and utility functions are also structured, using decision trees. In standard policy iteration, the value of the candidate policy is computed on each iteration by solving a system of jSj linear equations (step 2 in Table2 ), which is computationally prohibitive for large real-world planning problems. Modified policy iteration replaces this step with an iterative approximation of... ..."

### Table 2: The policy iteration algorithm

"... In PAGE 18: ... The representation of the policy and utility functions are also structured, using decision trees. In standard policy iteration, the value of the candidate policy is computed on each iteration by solving a system of jSj linear equations (step 2 in Table2 ), which is computationally prohibitive for large real-world planning problems. Modified policy iteration replaces this step with an iterative approximation of the value function V #19 by a series of value functions V 0;V 1; .... ..."

### Table 1 Iterative algorithms classification scheme

2000

"... In PAGE 4: ...Our new iterative algorithm, intensive search algorithm, is based on the non-greedy strat- egy, but it is not a stochastic algorithm. It is a non-greedy deterministic algorithm (see Table1 ). The key idea of the intensive search algorithm is that movies to the solutions, which increase (deteriorate) objective function value are permissible, in contrast to the greedy algorithms, where only the movies, which decrease objective function value are permissible.... ..."

### TABLE I FIRST TIER: THE ITERATIVE ALGORITHM

2006

Cited by 12

### TABLE I FIRST TIER: THE ITERATIVE ALGORITHM

2006

Cited by 12