### Table V reports some decidability results, depending on the structure of the considered program. For IACMIs satisfying these properties, reachability is decidable. For example, reachability is decidable in the Bell and La Padula and NIST models, as stated by the following proposition.

2003

Cited by 58

### Table 3: A Routing Algorithm for n k Diagonal Mesh, k 2n + 1. 3.3 Diameter Analysis Besides facilitating the development of routing algorithms, the propositions and corol- laries described in Section 3.2 also allow formulation of the diameter of a diagonal mesh. We present such formulation in the following proposition: Proposition 6 For an N = n k diagonal mesh network, assume n; k are odd, k n and Dd is the diameter.

1994

"... In PAGE 17: ... Based on these propositions and corollaries, we summarized routing algorithms for diagonal mesh network with N = n k nodes in Tables 2 and 3. Table 2 corresponds to n k lt; 2n and Table3 to k 2n. These routing algorithms identify all optimal directions and shortest path length between any two nodes for the two cases.... ..."

Cited by 8

### Table 1: Minimal index of a 1-reducible subgroup in a nite primitive irreducible subgroup of PGL(4;C) As a rst result we obtain the following : Proposition 1. If an irreducible linear di erential equa-

2001

"... In PAGE 2: ... Thus, for each group G given by Blichfeldt, we can compute the minimal index of a 1-reducible subgroup of G=Z(G), as explained in Section 3 of [14]. Computations were done with the computer algebra system Magma [2] and results appear in the Table1 . Notations of the groups are those used by Blichfeldt (c.... ..."

Cited by 2

### Table 1: Expected size of recovered relation (jrj = 10; n = 12; p = 4; j j = 2) There are, as yet, no completely general results concerning the expected value of jr j in the overlapping case: the situation is apparently very complex and depends on the exact structure of . However, the following Proposition provides a useful formula for calculating this expected value: Proposition 6.1

"... In PAGE 17: ... For each constraint there are j jp possible values, so if r may be approximated by a random selection of tuples, we may use elementary probability arguments to show that: P (w[Sj] 2 Sj(r)) = 1 ? (1 ? 1=j jp)jrj Assuming, for the moment, that the constraints all act independently, we obtain the following expression for the expected size of the recovered relation, E(jr j) (see [20]): E(jr j) = j jn(1 ? (1 ? 1=j jp)jrj)q (2) This expression may be a useful approximation when the Si do not overlap, but, is much too optimistic for the cases we are interested in, which have a high degree of overlap. Table1 compares the values obtained from Equation 2 with the results of simulations for various values of q. It can be seen that the predicted values are much too small for larger values of q.... ..."

### lable propositions, we want to define goals so that an agent is required to do only those things within its control. A first attempt might simply be to restrict the ideal goal set as defined above to controllable propositions. The following example shows this to be inadequate.

1994

Cited by 157

### Table 4.2: Term reduction axioms 4.1 Proposition. The reduction of sequential composition is completely characterised by the following axioms:

### Table 3: Summary of Propositional Logic Theorem Provers

1996

"... In PAGE 30: ....1.1.5 Summary of Propositional logic theorem proving The following Table3 is a summary of the theorem provers just described. The information is based on readings from [17, 19, 16, 5, 12]... ..."

### Table 1: Summary of fragments of Bounded Arithmetic We will need the following easy generalization of [2, Theorem 5] to our setting (see [11]): Proposition 2.1. For i 1, SSi+1 2

1994

Cited by 33

### Table 1. Relaxed propositional heuristic.

2003

"... In PAGE 10: ... Solving relaxed plans can efficiently be done by building a relaxed problem graph, followed by a greedy plan generation process. Table1 depicts the implementation of the plan construction and the solution extraction phase. The first phase constructs the layered plan graph identical to the first phase of Graphplan [2].... ..."

Cited by 16