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[4] but it was limited to comparison. The paper takes the example of Chess to apply GA and proposes a new technique to apply GA to machine learning which can substitute the existing methodologies .The work proposed is shown to be robust and thus making the learning a natural process rather than an algorithmic one. The paper relies on the randomness of GAs… (More)

- Harsh Bhasin, Neha Singla
- 2012

—Subset Sum Problem (SSP) is an NP Complete problem which finds its application in diverse fields. The work suggests the solution of above problem with the help of genetic Algorithms (GAs). The work also takes into consideration, the various attempts that have been made to solve this problem and other such problems. The intent is to develop a generic… (More)

Manual Test Data Generation is an expensive, error prone and tedious task. Therefore, there is an immediate need to make the automation of this process as efficient and effective as possible. The work presented intends to automate the process of Test Data Generation with a goal of attaining maximum coverage. A Cellular Automata system is discrete in space… (More)

— An idea of the values between which the roots of the algebraic equation lie is needed in both bisection method and other numerical methods for finding out the roots. Therefore, a method to suggest them is required. Finding them is a search process, so Genetic Algorithms (GA) can be used for the above task as GA's are theoretically and empirically proven… (More)

Test Data Generation is an intricate process which requires intensive manual labor and thus a lot of project time. There is an immediate need of finding out an effective technique for automating the process as manual Test Data Generation escalates the project cost. The paper proposes the use of Artificial Life in generating and minimizing the Test Cases.… (More)

Test Data Generation is the soul of automated testing. The dream of having efficient and robust automated testing software can be fulfilled only if the task of designing a robust automated test data generator can be accomplished. In the work we explore the gaps in the existing techniques and intend to fill these gaps by proposing new algorithms. The… (More)

- Harsh Bhasin, Neha Singla
- 2012

N – Puzzle problem is an important problem in mathematics and has implications in Artificial Intelligence especially in gaming. The work presented reviews the previous attempts to solve this problem. A formal definition of the problem has been presented. The reason why it is considered as NP hard problem and why Genetic Algorithms (GAs) is applied has been… (More)

The problem of finding a minimum vertex cover is an NP hard optimization problem. Some approximation algorithms for the problem have been proposed but most of them are neither optimal nor complete. The work proposes the use of the theory of natural selection via Genetic Algorithms (GAs) for solving the problem. The proposed work has been tested for some… (More)

— Regression testing is an immensely important process in the maintenance phase. The prioritization of test case becomes all the more important owing to the fact that it is not feasible to run all the test cases after each and every change. The proposed work dwells on the power of fuzzy expert system to make decisions which are better than the normal expert… (More)

- Harsh Bhasin, Rohan Mahajan
- 2012

Maximum Clique Problem (MCP) is an NP Complete problem which finds its application in diverse fields. The work suggests the solution of above problem with the help of Genetic Algorithms (GAs). The work also takes into consideration, the various attempts that have been made to solve this problem and other such problems. The intend is to develop a generic… (More)