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What is Ant Algorithm

Handbook of Research on Nature-Inspired Computing for Economics and Management
Essentially, a reinforcement learning algorithm. In an ant algorithm, points that are good candidates for a solution to a problem get reinforced over time. When the algorithm terminates, the points that have been reinforced the most are selected as the solution(s) to the problem.
Published in Chapter:
Efficient Searching in Peer-to-Peer Networks Using Agent-Enabled Ant Algorithms
P. Dasgupta (University of Nebraska, USA)
DOI: 10.4018/978-1-59140-984-7.ch047
In this chapter we describe a mechanism to search for resources in unstructured peer-to- peer (P2P) networks using ant algorithms implemented through software agents. Traditional resource search algorithms in P2P networks use an uninformed or blind search among the various nodes of the network. In contrast, the resource search algorithm described in this chapter performs an informed search using the ant-based heuristic. In our algorithm, ants, implemented as software agents, are created in response to a user’s resource search query. An ant reinforces the route that yields a successful search for directing ants in the future towards nodes with higher probability of locating resources. We describe and compare different reinforcement strategies used by ants to perform efficient resource search in P2P networks.
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More Results
A New Way to Reorganize a Productive Department in Cells
Solution algorithm based on the simulation of self-organized colony of biologic ants according to the principles of the ant system paradigm, aimed at solving different types of problems within a reasonable amount of time.
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