### Table 1: Properties of qualitative influences

### Table 5: Qualitative influences: non-commutative, associative operators. Sign

2005

Cited by 5

### Table 5 Qualitative influences: non-commutative, associative operators

2004

### Table 6 Qualitative influences: non-commutative, non-associative operators; RA: right associative; LA: left associative Operator Sign

2004

"... In PAGE 15: ...o 0, i.e., S0(Cj,E)holds. a50 Finally, the results in Table6... In PAGE 16: ...nly in is able to satisfy I1, i.e., S+(Cj,E)holds. a50 The proofs for the other non-commutative, non-associative operators are similar; the results are given in Table6 . Tables 3, 5 and 6 clearly indicate that it is possible to model all possible qualitative influences among causes and effects, even if it is assumed that the interaction function is decomposable.... In PAGE 16: ... Suppose that this holds for bacteria A and B, then each of these would make the development of infection less likely, even though there could be circumstances where these bacteria turn pathogenic. Now, let C be a bacterium with only pathogenic strains, then the right-associative version of the implication ( Table6 ) would model this situation appropriately. For the qualitative influence of penicillin or chlortetracyclin on... ..."

### Table 4. Signs of qualitative influences for the non-commutative, non-associative operators; RA: right associative; LA: left associative.

2002

"... In PAGE 4: ... Suppose that this holds for bacteria A and B, then each of these would make the development of infection less likely, even though there could be circumstances where these bacteria turn pathogenic. Now, let C be a bacterium with only pathogenic strains, then the right-associative version of implication ( Table4 ) would model this situation appropriately. 3.... ..."

Cited by 6

### Table 6: Qualitative influences: non-commutative, non-associative operators; RA: right asso- ciative; LA: left associative.

2005

"... In PAGE 15: ...o 0, i.e. S0(Cj, E) holds. square Finally, the results in Table6 for the increasing order operator are proven. Proposition 6 Let B = (G, Pr) be a Bayesian network representing a causal independence model with decomposable interaction function f that is equal to the logical increasing order operator lt;.... In PAGE 15: ... Suppose that this holds for bacteria A and B, then each of these would make the development of infection less likely, even though there could be circumstances where these bacteria turn pathogenic. Now, let C be a bacterium with only pathogenic strains, then the right-associative version of implication ( Table6 ) would model this situation appropriately.... ..."

Cited by 5

### Table 7 Algorithmic description of decentralized optimization algorithm incorporating reduced-communication field evaluation. communication. The most basic method, used in Tab. 7, computes communi- cation frequency as a function of the weight along the influence graph edge. This requires each source to communicate with each field node (some more frequently than others). A more qualitative method forms equivalence classes of field nodes based on influence (iso-influences) for each source, and treats the regions equivalently with respect to communication frequency. Now communi- cation paths only exist between sources and regions. An even more qualitative method forms equivalence classes of field nodes based on which source has the strongest influence, again treating regions equivalently with respect to com- munication frequency. With this assignment, each source communicates only with its own region and with other sources, which pass information on to their regions.

2001

"... In PAGE 32: ... If a source only weakly affects a temperature node, we need not assign it much blame/credit for the error at that node. Table7 summarizes the new field-evaluation algorithm, and Figure 25 illus- trates the new data flow during control optimization. The frequency of source- field communication is proportional to the amount of influence.... ..."

Cited by 10

### Table 2: Qualitative Analysis of the Schemes.

"... In PAGE 11: ... The number of induced checkpoints is less compared to the LCCP scheme and the rollback propagation is less compared to the LAZY scheme. Table2 summarizes the role of system parameters in the checkpoint and the recovery cost; and the relative degree of its influence on the schemes is analyzed. 3.... ..."

### Table 2: Qualitative comparison of other location-tracking systems with Cricket.

2000

"... In PAGE 10: ... The rest of this section discusses three systems that influenced var- ious aspects of Cricket, and compares their relative benefits and limitations. Table2 summarizes the following discussion. 6.... ..."

Cited by 445

### Table 2: Qualitative comparison of other location-tracking systems with Cricket.

2000

"... In PAGE 10: ... The rest of this section discusses three systems that influenced var- ious aspects of Cricket, and compares their relative benefits and limitations. Table2 summarizes the following discussion. 6.... ..."

Cited by 445