投票理论研究现状及其展望

社会选择理论是研究如何表达和聚合个体选择的一门学问.而社会选择理论与计算机科学的融合产生了称为计算社会选择的交叉学科,该学科成为社会计算的重要研究内容之一,在人工智能、经济和计算性理论领域引起了轰动.其一方面引入了复杂性分析和算法设计等计算机学科中常用的技术来对社会选择机制进行研究;另一方面也通过引入社会选择理论中的概念来推动计算机技术的发展,特别是在多智能体系统研究中有着成功的应用.投票理论是计算社会选择中最重要的研究主题之一.首先介绍常见的投票方法以及投票理论的形式化框架;再对投票理论中所关心的操纵问题做分析;然后介绍在组合域上的投票;最后对其他相关问题作简要介绍,并对该领域未来的发展与应用做出展望.     

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.     

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.     

Algorithms for transitive closure

Let σ′(n) denote the number of all strongly connected graphs on the n-element set. We prove that σ′(n)?2ⁿ²·(1−n(n−1)/2ⁿ⁻¹). Hence the algorithm computing a transitive closure by a reduction to acyclic graphs has the expected time O(n²), under the assumption of uniform distribution of input graphs. Furthermore, we present a new algorithm constructing the transitive closure of an acyclic graph.     

Quantum lower bounds for the Goldreich-Levin problem

At the heart of the Goldreich-Levin theorem is the problem of determining an n-bit string a by making queries to two oracles, referred to as IP (inner product) and EQ (equivalence). The IP oracle, on input x, returns a bit that is biased towards a⋅x (the modulo two inner product of a with x) in the following sense. For a random x, the probability that IP(x)=a⋅x is at least . The EQ oracle, on input x, returns a bit specifying whether or not x=a. It has been shown that a quantum algorithm can solve this problem with O(1/?) IP and EQ queries, whereas any classical algorithm requires Ω(n/?²) such queries. Also, the quantum algorithm requires only O(n/?) auxiliary one- and two-qubit gates in addition to its queries. We show that the above quantum algorithm is optimal in terms of both EQ and IP queries. Specifically, Ω(1/?) EQ queries are necessary, and Ω(1/?) IP queries are necessary if the number of EQ queries is .     

The communication complexity of the Hamming distance problem

We investigate the randomized and quantum communication complexity of the Hamming Distance problem, which is to determine if the Hamming distance between two n-bit strings is no less than a threshold d. We prove a quantum lower bound of Ω(d) qubits in the general interactive model with shared prior entanglement. We also construct a classical protocol of O(dlogd) bits in the restricted Simultaneous Message Passing model with public random coins, improving previous protocols of O(d²) bits [A.C.-C. Yao, On the power of quantum fingerprinting, in: Proceedings of the 35th Annual ACM Symposium on Theory of Computing, 2003, pp. 77-81], and O(dlogn) bits [D. Gavinsky, J. Kempe, R. de Wolf, Quantum communication cannot simulate a public coin, quant-ph/0411051, 2004].     

A new algorithm for the largest empty rectangle problem

A rectangleA and a setS ofn points inA are given. We present a new simple algorithm for the so-called largest empty rectangle problem, i.e., the problem of finding a maximum area rectangle contained inA and not containing any point ofS in its interior. The computational complexity of the presented algorithm isO(n logn + s), where s is the number of possible restricted rectangles considered. Moreover, the expected performance isO(n · logn).     

Fixed-parameter algorithms for Kemeny rankings

The computation of Kemeny rankings is central to many applications in the context of rank aggregation. Given a set of permutations (votes) over a set of candidates, one searches for a “consensus permutation” that is “closest” to the given set of permutations. Unfortunately, the problem is NP-hard. We provide a broad study of the parameterized complexity for computing optimal Kemeny rankings. Besides the three obvious parameters “number of votes”, “number of candidates”, and solution size (called Kemeny score), we consider further structural parameterizations. More specifically, we show that the Kemeny score (and a corresponding Kemeny ranking) of an election can be computed efficiently whenever the average pairwise distance between two input votes is not too large. In other words, Kemeny Score is fixed-parameter tractable with respect to the parameter “average pairwise Kendall–Tau distance _da$d_a$”. We describe a fixed-parameter algorithm with running time 16^⌈_da⌉⋅poly$16^{\lceil d_a\rceil }\cdot poly$. Moreover, we extend our studies to the parameters “maximum range” and “average range” of positions a candidate takes in the input votes. Whereas Kemeny Score remains fixed-parameter tractable with respect to the parameter “maximum range”, it becomes NP-complete in the case of an average range of two. This excludes fixed-parameter tractability with respect to the parameter “average range” unless P=NP. Finally, we extend some of our results to votes with ties and incomplete votes, where in both cases one no longer has permutations as input.     

The hardness of the Expected Decision Depth problem

Given a function f over n binary variables, and an ordering of the n variables, we consider the Expected Decision Depth problem. Namely, what is the expected number of bits that need to be observed until the value of the function is determined, when bits of the input are observed according to the given order. Our main finding is that this problem is (essentially) #P-complete. Moreover, the hardness holds even when the function f is represented as a decision tree.     

多赢家投票理论的研究进展

随着智能时代的到来,集体决策的方式也在发生着改变,人们不再满足于单一的决策结果,需要多个赢家共同组成的委员会成为获胜集合,并将此集合应用于推荐系统、搜索引擎、政策表决以及企业决策等领域.多赢家投票理论最大的优点是决策成本低并且决策效率高,是非常优秀的集体决策方法.多赢家投票理论的研究核心在于找到适合不同应用场景的多赢家...     

Algorithms for four variants of the exact satisfiability problem

We present four polynomial space and exponential time algorithms for variants of the E S problem. First, an O(1.1120ⁿ) (where n is the number of variables) time algorithm for the NP-complete decision problem of E 3-S , and then an O(1.1907ⁿ) time algorithm for the general decision problem of E S . The best previous algorithms run in O(1.1193ⁿ) and O(1.2299ⁿ) time, respectively. For the #P-complete problem of counting the number of models for E 3-S we present an O(1.1487ⁿ) time algorithm. We also present an O(1.2190ⁿ) time algorithm for the general problem of counting the number of models for E S ; presenting a simple reduction, we show how this algorithm can be used for computing the permanent of a 0/1 matrix.     

Quantum Algorithms: Philosophical Lessons

I discuss the philosophical implications that the rising new science of quantum computing may have on the philosophy of computer science. While quantum algorithms leave the notion of Turing-Computability intact, they may re-describe the abstract space of computational complexity theory hence militate against the autonomous character of some of the concepts and categories of computer science.

On the All-Farthest-Segments problem for a planar set of points

In this note, we outline a very simple algorithm for the following problem: Given a set S of n points p₁,p₂,p₃,…,pn in the plane, we have O(n²) segments implicitly defined on pairs of these n points. For each point pi, find a segment from this set of implicitly defined segments that is farthest from pi. The time complexity of our algorithm is in O(nh+nlogn), where n is the number of input points, and h is the number of vertices on the convex hull of S.     

Algorithms for the car sequencing and the level scheduling problem

This paper deals with two most important problems arising in sequencing mixed-model assembly lines. One problem is to keep the line's workstations loads as constant as possible (the 'car sequencing problem') while the other is to keep the usage rate of all parts fed into the final assembly as constant as possible (the 'level scheduling problem'). The first problem is a difficult constraint-satisfaction problem while the second requires to optimize a nonlinear objective function. The contribution of this paper is twofold: First, we describe a branching scheme and bounding algorithms for the computation of feasible sequences for the car sequencing problem. Second, we present an algorithm which can optimize a level scheduling objective while taking care of the car sequencing constraints. Computational results are presented which show that feasible sequences can be obtained quickly for large problem instances.     

Tractability frontiers of the partner units configuration problem

The partner units problem (PUP) is an acknowledged hard benchmark problem for the Logic Programming community with various industrial application fields like surveillance, electrical engineering, computer networks or railway safety systems. Although it is already known for a while that the PUP is NP-complete in its general form, complexity for subproblems reflecting the real problems in industrial fields remained widely unclear so far. In this article we provide all missing complexity results. For the subclass of the PUP that belongs to the complexity class P we present a polynomial-time algorithm and give in-depth algorithmic complexity results.     

Complexity results for the horizontal bar packing problem

This paper deals with the packing of a grid by horizontal bars while respecting given orthogonal projections and several constraints of distance between the consecutive bars. We show that packing under a maximal or uniform distance is an NP-complete problem. We also give a polynomial time algorithm to solve the packing problem under a minimal distance.     

The language intersection problem for non-recursive context-free grammars

We prove that, given as input two context-free grammars, deciding non-emptiness of intersection of the two generated languages is PSPACE-complete if at least one grammar is non-recursive. The problem remains PSPACE-complete when both grammars are non-recursive and deterministic. Also investigated are generalizations of the problem to several context-free grammars, of which a certain number are non-recursive.     

The open capacitated arc routing problem

The Open Capacitated Arc Routing Problem (OCARP) is a NP-hard combinatorial optimization problem where, given an undirected graph, the objective is to find a minimum cost set of tours that services a subset of edges with positive demand under capacity constraints. This problem is related to the Capacitated Arc Routing Problem (CARP) but differs from it since OCARP does not consider a depot, and tours are not constrained to form cycles. Applications to OCARP from literature are discussed. A new integer linear programming formulation is given, followed by some properties of the problem. A reactive path-scanning heuristic, guided by a cost-demand edge-selection and ellipse rules, is proposed and compared with other successful CARP path-scanning heuristics from literature. Computational tests were conducted using a set of 411 instances, divided into three classes according to the tightness of the number of vehicles available; results reveal the first lower and upper bounds, allowing to prove optimality for 133 instances.