资源列表
ReinforcementLearning
- A matlab code for a reinforment learning routing problem-A Matlab code for a reinforment learning ro uting problem
rtrl.tar
- two Matlab functions for initializing and training a recurrent neural network -two Matlab functions for initializing and training a recurrent neural network
antnet-4.0-src
- use swarm intelligence to simulate network routings in omnet-use swarm intelligence to simulate networ k routings in omnet
GeneticAntAlgorithms
- use genetic ant algorithm to slove TSP problem-use genetic algorithm to slove ant TSP ty B'Tselem,
QACSMATLAB
- use swarm intelligence algorithm to slove travelling sales man problems in matlab-use swarm intelligence algorithm to slove traveling sales man problems in Matlab
MIT_AI
- 美国麻省理工大学教授人工智能的课件以及课后的习题相关-American University professor of artificial intelligence at MIT courseware and the exercises related to the after-school
GAcodes
- An Introduction to Genetic Algorithms for Scientists and Engineers By David Coley, World Scientific Press, 1999 (US$28 / £ 19.04) 书中的算法源程序-An Introduction to Genetic Algorithms for Scientists and Engineers By David Coley, World Scientific Pr
RaoBlackwellisedParticleFilteringforDynamicConditi
- The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient stat
ReversibleJumpMCMCSimulatedAnneaing
- This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global se
SequentialSamplingImportanceResampling(SIR)
- this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.-this demo is to show you how to implement a ge neric SIR (a.k.a. pa
MCRGSA
- MCRGSA------组播路由问题遗传模拟退火算法 ％M-----------遗传算法进化代数 ％N-----------种群规模，取偶数 ％Pm----------变异概率调节参数 ％K-----------同一温度下状态跳转次数 ％t0----------初始温度 ％alpha-------降温系数 ％beta--------浓度均衡系数 ％ROUTES------备选路径集 ％Num---------到各节点的备选路径数目 ％Cost-------
c4[1].5r8
- 用于数据挖掘的分类算法,基于c语言的,一个c4.5分类算法-used for the classification of data mining algorithms, based on the c language, a classification algorithm c4.5