A Novel Parser Design Algorithm Based on Artificial Ants
Deepyaman Maiti, Ayan Acharya, Amit Konar, Janarthanan Ramadoss

TL;DR
This paper introduces a new parser design using Ant Colony Optimization that efficiently handles ambiguous grammars and finds optimal parsing paths by mimicking ant behavior, eliminating complex set calculations.
Contribution
It presents a novel bottom-up parser algorithm based on artificial ants that directly uses ambiguous grammars and discovers optimal parsing paths through pheromone-guided search.
Findings
Effective parsing of ambiguous and redundant grammars.
Ability to determine string membership in the language.
Finds shortest derivation paths when multiple options exist.
Abstract
This article presents a unique design for a parser using the Ant Colony Optimization algorithm. The paper implements the intuitive thought process of human mind through the activities of artificial ants. The scheme presented here uses a bottom-up approach and the parsing program can directly use ambiguous or redundant grammars. We allocate a node corresponding to each production rule present in the given grammar. Each node is connected to all other nodes (representing other production rules), thereby establishing a completely connected graph susceptible to the movement of artificial ants. Each ant tries to modify this sentential form by the production rule present in the node and upgrades its position until the sentential form reduces to the start symbol S. Successful ants deposit pheromone on the links that they have traversed through. Eventually, the optimum path is discovered by the…
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