香港六合彩-六合彩

Natural Computation CO637 Swarm Intelligence III: Ant Colony Optimisation applications Comparing PSO and ACO Alex Freitas

Recap - basic ideas of Ant Colony Optimisation (ACO) algorithms ,[object Object],[object Object],[object Object],[object Object]

Recap - main elements in the design of an ACO algorithm ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object], 1   1  2   2 1 2 ? component 1 component 2

Applying Ant Colony Optimisation (ACO) to Data Network Routing: AntNet ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

AntNet’s main data structure A pheromone matrix T associated with each node i of the network Each element  ijd of T indicates the desirability for an ant in node i and with destination node d to move to node j  i,1,1 . . .  i,1,n  i,N(i),1 . . .  i,N(i),n destination nodes . . . . . . . . . Neighbour nodes Structure of transition matrix at node i : N(i) is the number of neighbours of node i n is the total number of nodes in the network

The AntNet Algorithm for Data Network Routing (1) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

The AntNet Algorithm for Data Network Routing (2) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],E.g., forward ant 1  6, backward ant 6  1

The AntNet Algorithm for Data Network Routing (3) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

An application of ACO in automated customer support (1) ,[object Object],[object Object],[object Object],[object Object]

An Application of ACO in automated customer support (2) ,[object Object],[object Object],[object Object],[object Object],[object Object]

An Application of ACO in automated customer support (3) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

An Application of ACO in automated customer support (4) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

An Application of ACO in automated customer support (5) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Human users are “foraging” for best answer Move from answer A 1 to answer A 2 : increasing “pheromone” (score) in the link

An Application of ACO in automated customer support (6) ,[object Object],[object Object],[object Object]

Summary about ACO applications ,[object Object],[object Object],[object Object],[object Object],[object Object]

Comparing PSO and ACO (1) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Comparing PSO and ACO (2) ,[object Object],[object Object],[object Object],[object Object]

References M. Dorigo and T. Stutzle. Ant Colony Optimization . MIT Press, 2004. N. Monmarche, M. Slimane, G. Venturini. AntClass: discovery of clusters in numeric data by an hybridization of an ant colony with the Kmeans algorithm. Internal Report No. 213 , E3i. Laboratoire d’Informatique. Universite de Tours, France. Jan. 1999. (URL: citeseer.ist.psu.edu/559169.html) D. Warner, J.N. Richter, S.D. Durbin and B. Banerjee. Mining user session data to facilitate user interaction with a customer service knowledge base in RightNow Web. Proc. 7th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining (KDD-2000) , pp. 467-472. ACM Press, 2001.

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