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We pursue the program of exposing the intrinsic mathematical structure of the “space of a proofs” of a logical system [AJ94b]. We study the case of Multiplicative-Additive Linear Logic (MALL). We use tools from Domain theory to develop a semantic notion of proof net for MALL, and prove a Sequentialization Theorem. We also give an interactive criterion for strategies, formalized in the same Domain-theoretic setting, to come from proofs, and show that a “semantic proof structure” satisfies the geometric correctness criterion for proof-nets if and only if it satisfies the interactive criterion for strategies. We also use the Domain-theoretic setting to give an elegant compositional account of Cut-Elimination. This work is a continuation of previous joint work with Radha Jagadeesan [AJ94b] and Paul-André Melliès [AM99].

We consider zero-sum repeated games with omega-regular goals. Such hgames are played on a finite state space over an infinite number of rounds: at every round, the players select moves, either in turns or simultaneously; the current state and the selected moves determine the successor state. A play of the game thus consists in an infinite path over the state space or, if randomization is present, in a probability distribution over paths. Omega-regular goals generalize the class of regular goals (those expressible by finite automata) to infinite sequences, and include many well-known goals, such as the reachability and safety goals, as well as the Büchi and parity goals.

The algorithms for solving repeated games with omega-regular goals can be broadly divided into and algorithms. Enumerative algorithms consider each state individually; currently, they achieve the best worst-case complexity among the known algorithms. Symbolic algorithms compute in terms of sets of states, or functions from states to real numbers, rather than single states; such sets or functions can often be represented symbolically (hence the name of the algorithms). Even though symbolic algorithms often cannot match the worst-case complexity of the enumerative algorithms, they are often efficient in practice.

We illustrate how symbolic algorithms provide uniform solutions of many classes of repeated games, from turn-based, non-randomized games where at each state one of the players can deterministically win, to concurrent and randomized games where the ability to win must be characterized in probabilistic fashion. We also show that the symbolic algorithms, and the notation used to express them, are closely related to which provide a notion of distance between game states. Roughly, the distance between two states measures how closely a player can match, from one state, the ability of winning from the other state with respect to any omega-regular goal.

Axiom systems are ubiquitous in mathematical logic, one famous example being first order Peano Arithmetic. Foundational questions asked about axiom systems comprise analysing their provable consequences, describing their class of provable recursive functions (i.e. for which programs can termination be proven from the axioms), and characterising their consistency strength. One branch of proof theory, called Ordinal Analysis, has been quite successful in giving answers to such questions, often providing a unifying approach to them. The main aim of Ordinal Analysis is to reduce such questions to the computation of so called proof theoretic ordinals, which can be viewed as abstract measures of the complexity inherent in axiom systems. Gentzen’s famous consistency proof of arithmetic [Gen35, Gen38] using transfinite induction up to (a notation of) Cantor’s ordinal , can be viewed as the first computation of the proof theoretic ordinal of Peano Arithmetic.

The satisfaction problem for first-order logic, namely to decide, given a finite structure and a first-order formula , whether or not is known to be PSpace-complete. In terms of parameterized complexity, where the length of is taken as the parameter, the problem is AW[ ⋆ ]-complete and therefore not expected to be fixed-parameter tractable (FPT). Nonetheless, the problem is known to be FPT when we place some structural restrictions on A. For some restrictions, such as when we place a bound on the treewidth of , the result is obtained as a corollary of the fact that the satisfaction problem for monadic second-order logic (MSO) is FPT in the presence of such restriction [1]. This fact is proved using automata-based methods. In other cases, such as when we bound the degree of , the result is obtained using methods based on the locality of first-order logic (see [3]) and does not extend to MSO. We survey such fixed-parameter tractability results, including the recent [2] and explore the relationship between methods based on automata, locality and decompositions.

Automata on infinite objects were the key to the solution of several fundamental decision problems in mathematics and logic. Today, automata on infinite objects are used for formal specification and verification of reactive systems. The practical importance of automata in formal methods has motivated a re-examination of the blow up that translations among different types of automata involve. For most translations, the situation is satisfying, in the sense that even if there is a gap between the upper and the lower bound, it is small. For some highly practical cases, however, the gap between the upper and the lower bound is exponential or even larger. The article surveys several such frustrating cases, studies features that they share, and describes recent efforts (with partial success) to close the gaps.

We present a practical algorithm for computing exact least solutions of systems of equations over the rationals with addition, multiplication with positive constants, minimum and maximum. The algorithm is based on strategy improvement combined with solving linear programming problems for each selected strategy. We apply our technique to compute the abstract least fixpoint semantics of affine programs over the relational template constraint matrix domain [20]. In particular, we thus obtain practical algorithms for computing the abstract least fixpoint semantics over the zone and octagon abstract domain.

We study infinite games where one of the players always has a positional (memory-less) winning strategy, while the other player may use a history-dependent strategy. We investigate winning conditions which guarantee such a property for all arenas, or all finite arenas. Our main result is that this property is decidable in single exponential time for a given prefix independent -regular winning condition. We also exhibit a big class of winning conditions (XPS) which has this property.

The question of the exact complexity of solving parity games is one of the major open problems in system verification, as it is equivalent to the problem of model-checking the modal -calculus. The known upper bound is NP∩co-NP, but no polynomial algorithm is known. It was shown that on tree-like graphs (of bounded tree-width and DAG-width) a polynomial-time algorithm does exist. Here we present a polynomial-time algorithm for parity games on graphs of bounded clique-width (class of graphs containing e.g. complete bipartite graphs and cliques), thus completing the picture. This also extends the tree-width result, as graphs of bounded tree-width are a subclass of graphs of bounded clique-width. The algorithm works in a different way to the tree-width case and relies heavily on an interesting structural property of parity games.

Church’s Problem (1962) asks for the construction of a procedure which, given a logical specification on sequence pairs, realizes for any input sequence an output sequence such that (,) satisfies . Büchi and Landweber (1969) gave a solution for MSO specifications in terms of finite-state automata. We address the problem in a more general logical setting where not only the specification but also the solution is presented in a logical system. Extending the result of Büchi and Landweber, we present several logics such that Church’s Problem with respect to has also a solution in , and we discuss some perspectives of this approach.

Although Cai, Fürer and Immerman have shown that fixed-point logic with counting (IFP+C) does not express all polynomial-time properties of finite structures, there have been a number of results demonstrating that the logic does capture on specific classes of structures. Grohe and Mariño showed that IFP+C captures on classes of structures of bounded treewidth, and Grohe showed that IFP+C captures on planar graphs. We show that the first of these results is optimal in two senses. We show that on the class of graphs defined by a non-constant bound on the tree-width of the graph, IFP+C fails to capture . We also show that on the class of graphs whose local tree-width is bounded by a non-constant function, IFP+C fails to capture . Both these results are obtained by an analysis of the Cai–Fürer–Immerman (CFI) construction in terms of the treewidth of graphs, and cops and robber games; we present some other implications of this analysis. We then demonstrate the limits of this method by showing that the CFI construction cannot be used to show that IFP+C fails to capture on proper minor-closed classes.