On P versus NP $ \cap $ co-NP for decision trees and read-once branching programs

It is known that if a Boolean function f in n variables has a DNF and a CNF of size then f also has a (deterministic) decision tree of size exp(O(log n log² N)). We show that this simulation cannot be made polynomial: we exhibit explicit Boolean functions f that require deterministic trees of size exp where N is the total number of monomials in minimal DNFs for f and ?f. Moreover, we exhibit new examples of explicit Boolean functions that require deterministic read-once branching programs of exponential size whereas both the functions and their negations have small nondeterministic read-once branching programs. One example results from the Bruen—Blokhuis bound on the size of nontrivial blocking sets in projective planes: it is remarkably simple and combinatorially clear. Other examples have the additional property that f is in AC⁰. Received: June 5 1997.     

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 characterization of average case communication complexity

It is well known that the average case deterministic communication complexity is bounded below by an entropic quantity, which one would now call deterministic information complexity. In this paper we show a corresponding upper bound. We also improve known lower bounds for the public coin Las Vegas communication complexity by a constant factor.     

Kolmogorov complexity and combinatorial methods in communication complexity

We introduce a method based on Kolmogorov complexity to prove lower bounds on communication complexity. The intuition behind our technique is close to information theoretic methods.We use Kolmogorov complexity for three different things: first, to give a general lower bound in terms of Kolmogorov mutual information; second, to prove an alternative to Yao’s minmax principle based on Kolmogorov complexity; and finally, to identify hard inputs.We show that our method implies the rectangle and corruption bounds, known to be closely related to the subdistribution bound. We apply our method to the hidden matching problem, a relation introduced to prove an exponential gap between quantum and classical communication. We then show that our method generalizes the VC dimension and shatter coefficient lower bounds. Finally, we compare one-way communication and simultaneous communication in the case of distributional communication complexity and improve the previous known result.     

Traced communication complexity of cellular automata

We study cellular automata with respect to a new communication complexity problem: each of two players know half of some finite word, and must be able to tell whether the state of the central cell will follow a given evolution, by communicating as little as possible between each other. We present some links with classical dynamical concepts, especially equicontinuity, expansivity, entropy and give the asymptotic communication complexity of most elementary cellular automata.     

The BNS-Chung criterion for multi-party communication complexity

The "Number on the Forehead" model of multi-party communication complexity was first suggested by Chandra, Furst and Lipton. The best known lower bound, for an explicit function (in this model), is a lower bound of , where n is the size of the input of each player, and k is the number of players (first proved by Babai, Nisan and Szegedy). This lower bound has many applications in complexity theory. Proving a better lower bound, for an explicit function, is a major open problem. Based on the result of BNS, Chung gave a sufficient criterion for a function to have large multi-party communication complexity (up to ). In this paper, we use some of the ideas of BNS and Chung, together with some new ideas, resulting in a new (easier and more modular) proof for the results of BNS and Chung. This gives a simpler way to prove lower bounds for the multi-party communication complexity of a function. Received: December 12, 1997.     

Partition arguments in multiparty communication complexity

Consider the “Number in Hand” multiparty communication complexity model, where k players holding inputs x₁,…,x_k∈{0,1}ⁿ communicate to compute the value f(x₁,…,x_k) of a function f known to all of them. The main lower bound technique for the communication complexity of such problems is that of partition arguments: partition the k players into two disjoint sets of players and find a lower bound for the induced two-party communication complexity problem.In this paper, we study the power of partition arguments. Our two main results are very different in nature:

(i)

For randomized communication complexity, we show that partition arguments may yield bounds that are exponentially far from the true communication complexity. Specifically, we prove that there exists a 3-argument function f whose communication complexity is Ω(n), while partition arguments can only yield an Ω(logn) lower bound. The same holds for nondeterministiccommunication complexity.

(ii)

For deterministic communication complexity, we prove that finding significant gaps between the true communication complexity and the best lower bound that can be obtained via partition arguments, would imply progress on a generalized version of the “log-rank conjecture” in communication complexity. We also observe that, in the case of computing relations (search problems), very large gaps do exist.

We conclude with two results on the multiparty “fooling set technique”, another method for obtaining communication complexity lower bounds.     

On the complexity of one-shot translational separability

The problem of deciding whether 2- or 3-dimensional objects can be separated by a sequence of arbitrary translational motions is known to have exponential lower bounds. However, under certain restrictions on the type of motions, polynomial time bounds have been shown. An example is finding a subset of the parts that is removable by a single translation. In this case, the main restriction is that all selected parts are required to be removed in the same direction and with the same velocity. It was an open question whether the polynomial time bound can be achieved if more than a single velocity is allowed for the moving parts. In this paper, we answer this question by proving that such ‘multi-handed’ separability problems are NP-hard.     

On the complexity of digraph packings

Let be a fixed collection of digraphs. Given a digraph H, a -packing of H is a collection of vertex disjoint subgraphs of H, each isomorphic to a member of . For undirected graphs, Loebl and Poljak have completely characterized the complexity of deciding the existence of a perfect -packing, in the case that consists of two graphs one of which is a single edge on two vertices. We characterize -packing where consists of two digraphs one of which is a single arc on two vertices.     

On the complexity of case-based planning

This paper analyses the computational complexity of problems related to case-based planning: planning when a plan for a similar instance is known, and planning from a library of plans. It is proven that planning from a single case has the same complexity than generative planning (i.e. planning ‘from scratch’); using an extended definition of cases, complexity is reduced if the domain stored in the case is similar to the one to search plans for. Planning from a library of cases is shown to have the same complexity. In both cases, the complexity of planning remains, in the worst case, PSPACE-complete.     

On complexity of single-minded auction

We consider complexity issues for a special type of combinatorial auctions, the single-minded auction, where every agent is interested in only one subset of the commodities.First, we present a matching bound on the communication complexity for the single-minded auction under a general communication model. Next, we prove that it is NP-hard to decide whether Walrasian equilibrium exists in a single-minded auction. Finally, we establish a polynomial size duality theorem for the existence of Walrasian equilibrium for the single-minded auction.     

On the complexity of graph self-assembly in accretive systems

We study the complexity of the Accretive Graph Assembly Problem (). An instance of consists of an edge-weighted graph G, a seed vertex in G, and a temperature τ. The goal is to determine if the graph G can be assembled by a sequence of vertex additions starting from the seed vertex. The edge weights model the forces of attraction and repulsion, and determine which vertices can be added to a partially assembled graph at the given temperature. A vertex can be added when the total weight to its already built neighbors in the graph is at least τ. The assembly process is sequential meaning that only one vertex can be added at a time. Our first result is that is NP-complete even on planar graphs with maximum degree 3 when edges have only two different types of weights. This resolves the complexity of in the sense that the problem is poly-time solvable when either the maximum degree is at most 2 or the number of distinct edge weights is one, and is NP-complete otherwise. Our second result is a dichotomy theorem that completely characterizes the complexity of on graphs with maximum degree 3 and two distinct weights: w _p and w _n . We give a simple system of linear constraints on w _p , w _n , and τ that determines whether the problem is NP-complete or is poly-time solvable. In the process of establishing this dichotomy, we give a poly-time algorithm to solve a non-trivial class of Finally, we consider the optimization version of where the goal is to assemble a largest-possible induced subgraph of the given input graph. We show that even on graphs that can be assembled and have maximum degree 3, it is NP-hard to assemble a (1/n ^1-ε)-fraction of the input graph for any here n denotes the number of vertices in G.     

On the complexity of extension checking in default logic

The complexity of deciding equivalence of a formula to an extension of a default theory is investigated for the Reiter, justified, constrained, and rational semantics.     

On the complexity of market equilibria with maximum social welfare

We consider the computational complexity of the market equilibrium problem by exploring the structural properties of the Leontief exchange economy. We prove that, for economies guaranteed to have a market equilibrium, finding one with maximum social welfare or maximum individual welfare is NP-hard. In addition, we prove that counting the number of equilibrium prices is #P-hard.     

On the complexity of approximating k-set packing

Given a k-uniform hypergraph, the Maximum k -Set Packing problem is to find the maximum disjoint set of edges. We prove that this problem cannot be efficiently approximated to within a factor of unless P = NP. This improves the previous hardness of approximation factor of by Trevisan. This result extends to the problem of k-Dimensional-Matching.     

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.     

Larger lower bounds on the OBDD complexity of integer multiplication

Integer multiplication as one of the basic arithmetic functions has been in the focus of several complexity theoretical investigations and ordered binary decision diagrams (OBDDs) are one of the most common dynamic data structures for Boolean functions. Recently, the question whether the OBDD complexity of the most significant bit of integer multiplication is exponential has been answered affirmatively. In this paper a larger general lower bound is presented using a simpler proof. Furthermore, we prove a larger lower bound for the variable order assumed to be one of the best ones for the most significant bit. Moreover, the best known lower bound on the OBDD complexity for the so-called graph of integer multiplication is improved.