### Table 3: The inclusion table. (iii) Trivial from (i) and (ii). 2 Figure 4 reports the diagram summarizing the relations among the main security properties we analyzed in both the trace-based and bisimulation- based approach. We need some further remarks: Proposition 4.10 The following hold: (i) SNNI 6 BNNI and (ii) BNNI 6 SNNI. Proof. (i) holds because E = :l:0 + :h:l:0 is such that E 2 SNNI and E 62 BNNI . To prove case (ii) it is su cient to consider agent E = h:l:0 which is BNNI but not SNNI. 2 Finally, Table 3 reports also all the needed counterexamples.

1994

Cited by 61

### Table 6: Notations for transformations.

2002

"... In PAGE 14: ... Forgetting has also been used to design update operators with valuable properties (Herzig amp; Rifi, 1999). Table6 summarizes the transformations we are interested in and their acronyms. The following proposition states what we know about the tractability of these transformations with respect to the identified target compilation languages.... ..."

Cited by 59

### Table 6: Notations for transformations.

2002

"... In PAGE 14: ... Forgetting has also been used to design update operators with valuable properties (Herzig amp; Rifi, 1999). Table6 summarizes the transformations we are interested in and their acronyms. The following proposition states what we know about the tractability of these transformations with respect to the identified target compilation languages.... ..."

Cited by 59

### Table 4: Open Regime: Payoff matrix for firm A in second-stage subgame when both firms have entered the market.

2005

"... In PAGE 10: ...1. The resulting payoffs allow to reduce the stage-two subgame, assuming market entry by both firms, to a matrix game as shown in Table4 in the Appendix. Concerning the equilibria of this subgame, the following proposition holds (proof: see Appendix A.... ..."

Cited by 3

### Table 1. Kleene apos;s three-valued propositional tables. U stands for unevaluable

"... In PAGE 11: ... This can be described as follows: { A ^ B is true at an instant i i both A and B are evaluable and true at i; { A ^ B is false at an instant i i either A is false (regardless of the possibility of evaluating B) or B is false (regardless of the possibility of evaluating A) at i; { A ^ B is not evaluable at i otherwise. This approach corresponds to adopting the Kleene apos;s truth tables of three-valued logic [10], which are shown in Table1 . The main feature of Kleene apos;s tables is that the value true or the value false is returned whenever possible.... ..."

### Table 1 contains the running times of algebraic and combinatorial adjacency test on some examples. It shows that the combinatorial test is almost always faster. A partial explanation for that is the following: One can expect the algebraic test to perform better for proving adjacency (exhibit d ? 2 linearly independent rows) and the combinatorial for proving nonadjacency (exhibit one extreme ray violating Proposition 7), but the number of tests executed on nonadjacent pairs is usually much larger.

"... In PAGE 19: ...Table1 . Comparison of Algebraic and Combinatorial Adjacency Tests test problems sizes Algebraic Test Combin.... ..."

### Table 2. (Adapted from [313]) Complexity of Horn Logic Programs Notation: The complexity results in the above table refer to worst case analysis for skeptical reasoning, i.e. to determining if a given literal is true in every canonical model (with respect to a particular semantics) of the program. For logic programs with no function symbols, the data complexity over an EDB E is presented. The notation used is the following: jPj denotes the length of the program P; jAj denotes the number of propositional letters in P; jEj denotes the total number of symbols that occur in the EDB E.

"... In PAGE 12: ... Schlipf [313] has written a comprehensive survey article that summarizes the results. Some of these results, taken from [313], are listed in Table2 . A user may wish to determine which semantics to be used based upon the complexity expected to nd answers to queries.... In PAGE 17: ... Schlipf [313] and Eiter and Gottlob [106] have written comprehen- sive survey articles that summarize the complexity results that are known for alternative semantics. Some of these results, taken from [104, 106], are listed in Table2 . A user may wish to determine the semantics to be used based upon the complexity expected to nd answers to queries.... ..."

### Table 11: Functions f; h and probabilistic function composition h f. 3.4 Probabilistic Semantics A condition is a set of sets of literals (or equivalently a propositional formula in disjunctive normal form) whose atoms are of the form g(x; y; cf) with cf being a real number in the interval [0; 1]. The set of all conditions is denoted by C. We restrict ourselves to bag functions of the following types f : X ! B(Y C)

1994

Cited by 2

### Table 1 below gives a list of all constants that we shall use in this paper, most of them named in a way that makes it easy to see which words they are supposed to formalise (the others will not directly translate words of English; their use will become apparent below). The constants in the flrst column of the table have types as indicated in the second column. The idea behind the type assignment7 is that the meaning of a sentence, a proposition, is a function that gives us a truth value in each world (and thus it is a function of type st), that the meaning of a predicate like planet is a function that gives a truth value if we feed it an individual and a world (type e(st)) and that an expression that expects an expression of type fi should be of type fifl if the result of combining it with such an expression should be of type fl. So, for example, not is of type (st)(st) since it expects a proposition in order to form another proposition with it; the name mary gives a sentence if it is followed by a predicate and may therefore be assigned type (e(st))(st).

"... In PAGE 10: ... Table1 : Some non-logical constants Some easy calculation shows that the following are terms of type st: 6The application of type logic to the formalisation of English discussed in this section beneflced greatly from Montague [1970a, 1970b, 1973]. In fact we can think of it as a streamlined form of Montague semantics.... ..."