By Susanne Albers, Alberto Marchetti-Spaccamela, Yossi Matias, Sotiris Nikoletseas, Wolfgang Thomas

The two-volume set LNCS 5555 and LNCS 5556 constitutes the refereed court cases of the thirty sixth overseas Colloquium on Automata, Languages and Programming, ICALP 2009, held in Rhodes, Greece, in July 2009.

The 126 revised complete papers (62 papers for music A, 24 for music B, and 22 for song C) provided have been rigorously reviewed and chosen from a complete of 370 submissions. The papers are grouped in 3 significant tracks on algorithms, automata, complexity and video games; on good judgment, semantics, thought of programming, in addition to on foundations of networked computation: versions, algorithms and knowledge management.

LNCS 5556 includes forty six contributions of tracks B and C chosen from 147 submissions in addition to 2 invited lectures.

This two-volume set lauches the hot subline of Lecture Notes in computing device technological know-how, entitled LNCS complicated study in Computing and software program technology (ARCoSS).

**Read or Download Automata, Languages and Programming: 36th International Colloquium, ICALP 2009, Rhodes, Greece, July 5-12, 2009, Proceedings, Part II PDF**

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**Additional info for Automata, Languages and Programming: 36th International Colloquium, ICALP 2009, Rhodes, Greece, July 5-12, 2009, Proceedings, Part II**

**Sample text**

We conclude this section by recalling that the above desirable properties of acyclic CSP instances have proﬁtably been exploited in various application scenarios. Indeed, besides their application in the context of Database Theory, they found applications in Game Theory [14,8], Knowledge Representation and Reasoning [21], and Electronic Commerce [13], just to name a few. 3 Generalizing Acyclicity Many attempts have been made in the literature for extending the good results about acyclic instances to relevant classes of nearly acyclic structures.

Gottlob, G. Greco, and F. Scarcello Weighted CSPs: Costs over Tuples Let us now turn to study a slight variation of the above scenario, where costs are associated with each tuple of the constraint relations, rather than with substitutions for individual variables. In fact, this is the setting of weighted CSPs, a well-known specialization of the more general valued CSP framework [30]. , wq , where I = Var , U, C with C = {C1 , C2 , . . , Cq } is a CSP instance, and where, for each tuple tv ∈ rv , wv (tv ) ∈ Q denotes the cost associated with tv .

1 Tree Decompositions For classes of instances having only binary constraints or, more generally, constraints whose scopes have a ﬁxed maximum arity, the most powerful structural method is based on the notion of treewidth. Deﬁnition 1 ([28]). A tree decomposition of a graph G = (V, E) is a pair T, χ , where T = (N, F ) is a tree, and χ is a labelling function assigning with each vertex p ∈ N a set of vertices χ(p) ⊆ V such that the following conditions are satisﬁed: (1) for each node b of G, there exists p ∈ N such that b ∈ χ(p); (2) for each edge (b, d) ∈ E, there exists p ∈ N such that {b, d} ⊆ χ(p); and, (3) for each node b of G, the set {p ∈ N | b ∈ χ(p)} induces a connected subtree of T (connectedness condition).