Artificial Intelligence and Management ScienceRobert W. Blanning |
Contents
Preface | 46 |
Engineering principles from natural multiagent systems | 69 |
Active training of backpropagation neural networks using the learning | 105 |
Copyright | |
6 other sections not shown
Common terms and phrases
AARIA adaptation adjacency matrix analysis anchor agent Anchor&Ascend application Artificial Intelligence assumptions attributes audit average backpropagation neural network behavior bottleneck resource buyer components computational constraint coordination crossover operation cycle disparity composition ratio distributed Distributed Artificial Intelligence domain due date Editors environment evaluation example experimental expert systems feeder carriage Figure function genetic algorithms heuristic hybrid approach hypotheses input integration interaction ISSDSS iteration job agents job shop scheduling knowledge base learning linear programming linear programming model machine learning market core metagraph metapath method module multiple experts neural network node Operations Research optimization organization organizational output performance problem solving procedure production represent resource agents roulette wheel selection scheduling problems sealed bid auction selection seller sequence simulated annealing solution stock price strategy structure tardiness techniques Theorem trading transaction valid variables weighted tardiness cost x₁