- title = "Social Programming: Investigations in Grammatical Swarm",
- author = "Finbar Leahy",
- school = "University of Limerick",
- year = "2005",
- type = "Master of Science in Software Engineering",
- address = "University of Limerick, Ireland",
- month = "16 " # oct,
- keywords = "genetic algorithms, genetic programming, grammatical evolution, grammatical swarm",
-
URL = "
https://finbarleahy.files.wordpress.com/2010/07/mastersdissertation.pdf",
- size = "129 pages",
- language = "en",
-
abstract = "This study details a series of investigations
examining a recently introduced form of automatic
programming called Social Programming. The Grammatical
Swarm algorithm is a form of Social Programming as it
uses Particle Swarm Optimisation, a social swarm
algorithm, for the automatic construction of computer
programs for the optimisation of continuous, non-linear
problems. An investigation into the performance effects
of two different quality Pseudo-Random Number
Generators (PRNG) on the Grammatical Swarm algorithm
was examined. The results demonstrate that the choice
of PRNG does, in fact, have a small effect of the
performance of the Grammatical Swarm, with the more
sophisticated PRNG producing better results on two of
the four problems analysed.
An investigations was conducted into the effects of increasing the size of the particle representations of the Grammatical Swarm algorithm, such that the hard-length vector constraint of all particles in the swarm was doubled from 100 to 200. The results demonstrated that this leads to a significant gain in performance.
This thesis also introduces a new variable-length form of the Grammatical Swarm algorithm. Thus, this can be considered a proof of concept study. It examines the possibility of constructing programs using a particles representations which are variable in length and it is referred to as the Variable-Length Grammatical Swarm. This newly developed algorithm extends earlier work on the fixed-length incarnation of Grammatical Swarm, where each individual represents choices of program construction rules, where these rules are specified using a Backus-Naur Form grammar. The results demonstrate that is possible to successfully generate programs programs using a variable-length Particle Swarm Algorithm. This investigation also examines the performance effects of increasing the initialisation size of the variable-length particles. The results demonstrate that the performance of the Variable-Length Grammatical Swarm can be increased by doubling the potential size of the particle representations. Furthermore, the evolution of size in the particle representations is examined. This investigation was conduced in an effort to determine if the the variable- length particles suffered from bloat, which is a common problem in other Evolutionary Algorithms that use variable-length vector representations. No evidence of bloat was found.
Based on an overall comparative review of the both the fixed-length and variable-length forms of Grammatical Swarm it is recommended that the simpler fixed-length Grammatical Swarm with particle representation sizes of 200 codons in length be adopted.",
- notes = "Supervisor: Dr. Michael O'Neill",
