Task reallocation in a multi-robot organization is a process that distributes a decomposed global task to individual robots. This process must be distributed and dynamic because it relies on critical information that can only be obtained during mission execution. This paper presents a representation for this challenging problem and proposes an algorithm that allows member robots to trade tasks ...

In this article, Hill Climbing (HC) and Estimation of Distribution Algorithm (EDA) are integrated to produce a hybrid intelligent algorithm for design of endlessly Single Mode Photonic Crystal Fibers (SMPCFs) structure with desired properties over the C communication band. In order to analyzing the fiber components, Finite Difference Frequency Domain (FDFD) solver is applied. In addition, a spe...

Our system for the Novelty Track at TREC 2004 looks beyond sentence boundaries as well as within sentences to identify novel, nonduplicative passages. It tries to identify text spans of two or more sentences that encompass mini-segments of new information. At the same time, we avoid any pairwise comparison of sentences, but rely on the presence of previously unseen terms to provide evidence of ...

In this paper, we propose an integrated Genetic Algorithm with Hill Climbing to solve the matrix bandwidth minimization problem, which is to reduce bandwidth by permuting rows and columns resulting in the nonzero elements residing in a band as close as possible to the diagonal. Many algorithms for this problem have been developed, including the wellknown CM and GPS algorithms. Recently, Marti e...

In this paper we present a new iterative method to solve the maximum satisfiability problem (MAX SAT). This one aims to find the best assignment for a set of Boolean variables that gives the maximum of verified clauses in a Boolean formula. Unfortunately, It is shown that the MAX SAT problem is NP complete if the number of variable per clause is higher than 3. Our approach called QHILLSAT is a ...

We discuss the relationships between three approaches to greedy heuristic search: best-first, hill-climbing, and beam search. We consider the design decisions within each family and point out their oft-overlooked similarities. We consider the following best-first searches: weighted A*, greedy search,

Even though hill climbing search (HCS) control is the simplest MPPT algorithm that does not require any prior knowledge of the system, it has the disadvantage of being slow in its response. This slowness in the response is due to the number of perturbations involved in climbing the hill and the settling time of the each perturbation. This paper proposes an improved HCS control, in which the nat...

We present a method for solving service allocation problems in which a set of services must be allocated to a set of agents so as to maximize a global utility. The method is completely distributed so it can scale to any number of services without degradation. We first formalize the service allocation problem and then present a simple hill-climbing, a global hillclimbing, and a bidding-protocol ...

This paper presents a real-coded memetic algorithm that applies a crossover hill-climbing to solutions produced by the genetic operators. On the one hand, the memetic algorithm provides global search (reliability) by means of the promotion of high levels of population diversity. On the other, the crossover hill-climbing exploits the self-adaptive capacity of real-parameter crossover operators w...

The restricted setting and uniformly prescribed hardware of the Sony Legged League of RoboCup provide an environment for testing algorithms on autonomous robots with a view towards possible applications in real world situations. In this study we show how two techniques Support Vector Machines and Hill Climbing can be applied to problems faced by the robots in this league. We use Support Vector ...