Some results on the computational complexity of symmetric connectionist networks

Connectionists models are currently being investigated actively by many researchers in artificial intelligence, information theory and computational neuroscience. These networks have been shown to be applicable to a wide range of domains such as content addressable memories, semantic nets, computer vision, natural language parsing, speech recognition, and approximation schemes for difficult optimization problems. In this paper, we address several basic problems related to the computational complexity of discrete Hopfield nets (connectionist networks with symmetric connections).This research was supported in part by AFOSR Grant No. AFOSR-89-1151 and NSF Grant No. IRI-88-09324.     

A computer-assisted optimal depth lower bound for nine-input sorting networks

It is demonstrated, using a combination of theoretical and experimental computer science, that there is no nine-input sorting network of depth six. If a nine-input sorting network of depth six exists, then there exists one with very special structure. There is an efficient algorithm for constructing and testing comparator networks of this form. This algorithm was implemented and executed on a supercomputer.This research was supported by NSF Grant CCR-8801659 and a Research Initiation Grant from the Pennsylvania State University.     

Alternation and the computational complexity of logic programs

We investigate the complexity of derivations from logic programs, and find it closely related to the complexity of computations of alternating Turing machines. In particular, we define three complexity measures over logic programs—goal-size, length, and depth—and show that goal-size is linearly related to alternating space, the product of length and goal-size is linearly related to alternating tree-size, and the product of depth and goal-size is linearly related to alternating time. The bounds obtained are simultaneous. As an application, we obtain a syntactic characterization of Nondeterministic Linear Space and Alternating Linear Space via logic programs.     

Computational complexity of sorting and joining relations withduplicates

It is shown that the existence of duplicate values in some attribute columns has a significant impact on the computational complexity of the sorting and joining operations. This is especially true when the number of distinct tuple values is a small fraction of the total number of tuples. The authors characterize a multirelation M (n, L) by its cardinality n and the number of distinct elements L it contains. Under this characterization, the worst time complexity of sorting such a multirelation with binary comparisons as basic operations is investigated. Upper and lower bounds on the number of three-branch comparisons needed to sort such a multirelation are established. Thereafter, the methodology used to study the complexity of sorting is applied to the natural join operation. It is shown that the existence of duplicate values in the join attribute columns can be exploited to reduce the computational complexity of the natural join operation     

Theories with self-application and computational complexity

Applicative theories form the basis of Feferman’s systems of explicit mathematics, which have been introduced in the 1970s. In an applicative universe, all individuals may be thought of as operations, which can freely be applied to each other: self-application is meaningful, but not necessarily total. It has turned out that theories with self-application provide a natural setting for studying notions of abstract computability, especially from a proof-theoretic perspective. This paper is concerned with the study of (unramified) bounded applicative theories which have a strong relationship to classes of computational complexity. We propose new applicative systems whose provably total functions coincide with the functions computable in polynomial time, polynomial space, polynomial time and linear space, as well as linear space. Our theories can be regarded as applicative analogues of traditional systems of bounded arithmetic. We are also interested in higher-type features of our systems; in particular, it is shown that Cook and Urquhart’s system is directly contained in a natural applicative theory of polynomial strength.     

Connectivity and concentration in airline networks: a complexity analysis of Lufthansa's network

Information, communication and transport networks have always been in a state of flux, while they also influence each other. Extensive research efforts have been made to investigate the dynamics in the structure and use of networks, for example, by means of network geometries, Small-World effects and Scale-Free phenomena. We will illustrate these new developments on the basis of airline network evolution. Using Lufthansa's networks as an example, this paper aims to show the empirical relevance of various network indicators – such as connectivity and concentration – for understanding changing patterns in airline network configurations. After an extensive discussion of various statistical results, a decision-aid method, viz. multi-criteria analysis, is used to investigate the robustness of our findings. The results highlight the actual strategic choices made by Lufthansa for its own network, as well in combination with its partners in Star Alliance.     

The computational complexity of ideal semantics

We analyse the computational complexity of the recently proposed ideal semantics within both abstract argumentation frameworks (afs) and assumption-based argumentation frameworks (abfs). It is shown that while typically less tractable than credulous admissibi-lity semantics, the natural decision problems arising with this extension-based model can, perhaps surprisingly, be decided more efficiently than sceptical preferred semantics. In particular the task of finding the unique ideal extension is easier than that of deciding if a given argument is accepted under the sceptical semantics. We provide efficient algorithmic approaches for the class of bipartite argumentation frameworks and, finally, present a number of technical results which offer strong indications that typical problems in ideal argumentation are complete for the class of languages decidable by polynomial time algorithms allowed to make non-adaptive queries to a C oracle, where C is an upper bound on the computational complexity of deciding credulous acceptance: C=np for afs and logic programming (lp) instantiations of abfs; for abfs modelling default theories.     

基于网管业务特征的负载均衡策略研究

根据用户管理业务的组织结构提出适合网管业务特征的负载均衡策略,描述了策略的算法和实现,并在原型系统中进行测试比较,验证了算法的有效性。     

On the computational complexity of coalitional resource games

We study Coalitional Resource Games (crgs), a variation of Qualitative Coalitional Games (qcgs) in which each agent is endowed with a set of resources, and the ability of a coalition to bring about a set of goals depends on whether they are collectively endowed with the necessary resources. We investigate and classify the computational complexity of a number of natural decision problems for crgs, over and above those previously investigated for qcgs in general. For example, we show that the complexity of determining whether conflict is inevitable between two coalitions with respect to some stated resource bound (i.e., a limit value for every resource) is co-np-complete. We then investigate the relationship between crgs and qcgs, and in particular the extent to which it is possible to translate between the two models. We first characterise the complexity of determining equivalence between crgs and qcgs. We then show that it is always possible to translate any given crg into a succinct equivalent qcg, and that it is not always possible to translate a qcg into an equivalent crg; we establish some necessary and some sufficient conditions for a translation from qcgs to crgs to be possible, and show that even where an equivalent crg exists, it may have size exponential in the number of goals and agents of its source qcg.     

On the computational complexity of combinatorial flexibility problems

The concept of flexibility – originated in the context of heat exchanger networks design – is associated with a substructure which allows the same optimal value on the substructure (for example an optimal flow) as in the whole structure, for all the costs in a given range of costs. In this work, we extend the concept of flexibility to general combinatorial optimization problems, and prove several computational complexity results in this new framework. Under some monotonicity conditions, we prove that a combinatorial optimization problem can be polynomially reduced to its associated flexibility problem. However, the minimum cut, maximum weighted matching and shortest path problems have NP-complete associated flexibility problems. In order to obtain polynomial flexibility problems, we have to restrict ourselves to combinatorial optimization problems on matroids.     

On the computational complexity of bisimulation, redux

Paris Kanellakis and the second author (Smolka) were among the first to investigate the computational complexity of bisimulation, and the first and third authors (Moller and Srba) have long-established track records in the field. Smolka and Moller have also written a brief survey about the computational complexity of bisimulation [ACM Comput. Surv. 27(2) (1995) 287]. The authors believe that the special issue of Information and Computation devoted to PCK50: Principles of Computing and Knowledge: Paris C. Kanellakis Memorial Workshop represents an ideal opportunity for an up-to-date look at the subject.     

On the computational complexity of weighted voting games

Coalitional games provide a useful tool for modeling cooperation in multiagent systems. An important special class of coalitional games is weighted voting games, in which each player has a weight (intuitively corresponding to its contribution), and a coalition is successful if the sum of its members’ weights meets or exceeds a given threshold. A key question in coalitional games is finding coalitions and payoff division schemes that are stable, i.e., no group of players has any rational incentive to leave. In this paper, we investigate the computational complexity of stability-related questions for weighted voting games. We study problems involving the core, the least core, and the nucleolus, distinguishing those that are polynomial-time computable from those that are NP-hard or coNP-hard, and providing pseudopolynomial and approximation algorithms for some of the computationally hard problems.     

On the computational complexity of qualitative coalitional games

We study coalitional games in which agents are each assumed to have a goal to be achieved, and where the characteristic property of a coalition is a set of choices, with each choice denoting a set of goals that would be achieved if the choice was made. Such qualitative coalitional games (qcgs) are a natural tool for modelling goal-oriented multiagent systems. After introducing and formally defining qcgs, we systematically formulate fourteen natural decision problems associated with them, and determine the computational complexity of these problems. For example, we formulate a notion of coalitional stability inspired by that of the core from conventional coalitional games, and prove that the problem of showing that the core of a qcg is non-empty is D^p₁-complete. (As an aside, we present what we believe is the first “natural” problem that is proven to be complete for D^p₂.) We conclude by discussing the relationship of our work to other research on coalitional reasoning in multiagent systems, and present some avenues for future research.     

Parameterized computational complexity of Dodgson and Young elections

We show that the two NP-complete problems of Dodgson Score and Young Score have differing computational complexities when the winner is close to being a Condorcet winner. On the one hand, we present an efficient fixed-parameter algorithm for determining a Condorcet winner in Dodgson elections by a minimum number of switches in the votes. On the other hand, we prove that the corresponding problem for Young elections, where one has to delete votes instead of performing switches, is W[2]-complete. In addition, we study Dodgson elections that allow ties between the candidates and give fixed-parameter tractability as well as W[2]-completeness results depending on the cost model for switching ties.     

The network complexity and the Turing machine complexity of finite functions

Summary Let L(f) be the network complexity of a Boolean function L(f). For any n-ary Boolean function L(f) let . Hereby p ranges over all relative Turing programs and ranges over all oracles such that given the oracle , the restriction of p to inputs of length n is a program for L(f). p is the number of instructions of p. T _p (n) is the time bound and S _p of the program p relative to the oracle on inputs of length n. Our main results are (1) L(f) O(TC(L(f))), (2) TC(f) O(L(f) ^{2 2+}) for every O.The results of this paper have been reported in a main lecture at the 1975 annual meeting of GAMM, April 2–5, Göttingen