Search results for "ComputingMethodologies_ARTIFICIALINTELLIGENCE"
showing 10 items of 46 documents
THE SHAPLEY-SOLIDARITY VALUE FOR GAMES WITH A COALITION STRUCTURE
2013
A value for games with a coalition structure is introduced, where the rules guiding cooperation among the members of the same coalition are different from the interaction rules among coalitions. In particular, players inside a coalition exhibit a greater degree of solidarity than they are willing to use with players outside their coalition. The Shapley value is therefore used to compute the aggregate payoffs for the coalitions, and the solidarity value to obtain the payoffs for the players inside each coalition.
A Novel Approach to Improve the Accuracy of Web Retrieval
2010
General purpose search engines utilize a very simple view on text documents: They consider them as bags of words. It results that after indexing, the semantics of documents is lost. In this paper, we introduce a novel approach to improve the accuracy of Web retrieval. We utilize the WordNet and WordNet SenseRelate All Words Software as main tools to preserve the semantics of the sentences of documents and user queries. Nouns and verbs in the WordNet are organized in the tree hierarchies. The word meanings are presented by numbers that reference to the nodes on the semantic tree. The meaning of each word in the sentence is calculated when the sentence is analyzed. The goal is to put each nou…
MRF Model-Based Approach for Image Segmentation Using a Chaotic MultiAgent System
2006
In this paper, we propose a new Chaotic MultiAgent System (CMAS) for image segmentation. This CMAS is a distributed system composed of a set of segmentation agents connected to a coordinator agent. Each segmentation agent performs Iterated Conditional Modes (ICM) starting from its own initial image created initially from the observed one by using a chaotic mapping. However, the coordinator agent receives and diversifies these images using a crossover and a chaotic mutation. A chaotic system is successfully used in order to benefit from the special chaotic characteristic features such as ergodic property, stochastic aspect and dependence on initialization. The efficiency of our approach is s…
Towards Multilevel Ant Colony Optimisation for the Euclidean Symmetric Traveling Salesman Problem
2015
Ant Colony Optimization ACO metaheuristic is one of the best known examples of swarm intelligence systems in which researchers study the foraging behavior of bees, ants and other social insects in order to solve combinatorial optimization problems. In this paper, a multilevel Ant Colony Optimization MLV-ACO for solving the traveling salesman problem is proposed, by using a multilevel process operating in a coarse-to-fine strategy. This strategy involves recursive coarsening to create a hierarchy of increasingly smaller and coarser versions of the original problem. The heart of the approach is grouping the variables that are part of the problem into clusters, which is repeated until the size…
A New Crowded Comparison Operator in Constrained Multiobjective Optimization for Capacitors Sizing and Siting in Electrical Distribution Systems
2005
This paper presents a new Crowded Comparison Operator (CCO) for NSGA-II to solve the Multiobjective and constrained problem of optimal capacitors placement in electrical distribution systems.
Some Aspects Regarding the Application of the Ant Colony Meta-heuristic to Scheduling Problems
2010
Scheduling is one of the most complex problems that appear in various fields of activity, from industry to scientific research, and have a special place among the optimization problems In our paper we present the results of our computational study i.e an Ant Colony Optimization algorithm for the Resource-Constrained Project Scheduling Problem that uses dynamic pheromone evaporation.
Experiments on a Prey Predators System
2003
The paper describes a prey-predators system devoted to perform experiments on concurrent complex environment. The problem has be treated as an optimization problem. The prey goal is to escape from the predators reaching its lair, while predators want to capture the prey. At the end of the 19th century, Pareto found an optimal solutions for decision problems regarding more than one criterion at the same time. In most cases this ‘Pareto-set’ cannot be determined analytically or the computation time could be exponential. In such cases, evolutionary Algorithms (EA) are powerful optimization tools capable of finding optimal solutions of multi-modal problems. Here, both prey and predators learn i…
Decision Making on Pareto Front Approximations with Inherent Nondominance
2011
t Approximating the Pareto fronts of nonlinear multiobjective optimization problems is considered and a property called inherent nondominance is proposed for such approximations. It is shown that an approximation having the above property can be explored by interactively solving a multiobjective optimization problem related to it. This exploration can be performed with available interactive multiobjective optimization methods. The ideas presented are especially useful in solving computationally expensive multiobjective optimization problems with costly function value evaluations. peerReviewed
Multiobjective ant colony search algorithm optimal electrical distribution system planning
2005
A dynamic multiobjective, MO, algorithm based on the ant colony search, the multiobjective ant colony search algorithm, MOACS, is presented. The application domain is that of dynamic planning for electrical distribution systems. A time horizon of H years has been considered during which the distribution system are modified according to the new internal (loads) and external (market, reliability, power quality) requirements. In this scenario, the objectives the Authors consider most important for utilities in strategical planning are: the quality requirement connected to the decrease of the expected number of interruptions per year and customer, in the considered time frame, and the choice fo…
First spatial isotopic separation of relativistic uranium projectile fragments
1994
Abstract Spatial isotopic separation of relativistic uranium projectile fragments has been achieved for the first time. The fragments were produced in peripheral nuclear collisions and spatially separated in-flight with the fragment separator FRS at GSI. A two-fold magnetic-rigidity analysis was applied exploiting the atomic energy loss in specially shaped matter placed in the dispersive central focal plane. Systematic investigations with relativistic projectiles ranging from oxygen up to uranium demonstrate that the FRS is a universal and powerful facility for the production and in-flight separation of monoisotopic, exotic secondary beams of all elements up to Z = 92. This achievement has …