27853127
Trajectory planning of cellular manipulator system using virus-evolutionary genetic algorithm
This paper deals with an application of a genetic algorithm based on a virus theory of evolution (VEGA) to trajectory planning of a cellular manipulator system. A cellular manipulator system is composed of a large number of autonomous parts and tools. The form of the cellular manipulator system is dynamically reconfigured according to its environment and given tasks. In this paper, the VEGA is applied to a trajectory planning problem. The VEGA realizes a horizontal propagation and a vertical inheritance of genetic information in a population. The main operator of the VEGA is a reverse transcription operator, which plays the roles of a crossover and a selection at the same time. Simulation results of trajectory planning shows that the VEGA generates a collision-free trajectory.
203664973
Hierarchical Fuzzy Reasoning.
34833211
Coordinative behavior by genetic algorithm and fuzzy in evolutionary multi-agent system
A strategy for motion planning of multiple robots as a multi-agent system is proposed. All the robots cannot communicate globally, but some robots can communicate locally and coordinate to avoid competition for public resources. In such systems, it is difficult for each robot to plan its motion effectively, while considering other robots. Therefore, each robot determines its motion selfishly, planning its motion while considering the known environment and using empirical knowledge. The robot also considers its unknown environment, which includes the other robots, in the empirical knowledge. The genetic algorithm is used to optimize the motion of the planning. Each robot iteratively acquires knowledge of its unknown environment, expressed by fuzzy logic, and the system behaves efficiently as an evolutionary process. As an illustration, path planning by multiple mobile robots is considered.<<ETX>>
3771321
Constructing Efficient Decision Trees by Using Optimized Numeric Association Rules
We propose an extension of an entropy-based heuristic of Quinlan [Q93] for constructing a decision tree from a large database with many numeric attributes. Quinlan pointed out that his original method (as well as other existing methods) may be ine cient if any numeric attributes are strongly correlated. Our approach o ers one solution to this problem. For each pair of numeric attributes with strong correlation, we compute a two-dimensional association rule with respect to these attributes and the objective attribute of the decision tree. In particular, we consider a family R of grid-regions in the plane associated with the pair of attributes. For R 2 R, the data can be split into two classes: data inside R and data outside R. We compute the region R opt 2 R that minimizes the entropy of the splitting, and add the splitting associated with R opt (for each pair of strongly correlated attributes) to the set of candidate tests in Quinlan's entropy-based heuristic. We give e cient algorithms for cases in which R is (1) x-monotone connected regions, (2) basedmonotone regions, (3) rectangles, and (4) rectilinear convex regions. The algorithm for the rst case has been implemented as a subsystem of SONAR(System for Optimized Numeric Association Rules) developed by the authors. Tests show that our approach can create small-sized decision trees. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment. Proceedings of the 22nd VLDB Conference Mumbai(Bombay), India, 1996
27867212
A decomposition of complete bipartite graphs into edge-disjoint subgraphs with star components
Abstract A subgraph F of a graph G is called a star-subgraph if each component of F is a star. In this note we show that the minimum number of star-subgraphs that partition the edges of K2n−1,2n−1 or K2n,2n, respectively, is n + 2.