An Artificial Life Simulation to Observe DNA Sequence Repeat Pattern

Abstract

This study presents an artificial life simulation to observe DNA sequence repeat pattern to observe probable repetitions of DNA sequence of an agent in future generations. This also includes research into recognizing patterns in repetitions and the ratio of unique and repetitive DNA sequences along with observing agent's evolution and life expectancy. We chose a small representative of life namely ‘agents'. The agents have sufficient intelligence to make survival decisions and can adapt to minor scenario changes. The 2D plane is optimized so that agents can move freely on the plane without clogging corners. The agents use diploid reproduction system and two-point crossover to produce offsprings. The agents also use simple learning algorithms and weighted random selection based movement logic. Simple logic that imitates Evolutionary processes further adapts the agents to their environment by making them more efficient. The DNA sequences are stored and activities of the agents of a population are monitored and logged accordingly in our system. After gathering data from successful sessions we analyze these data to observe patterns in repetitions of a previous DNA sequence and detect anomalies, observe life's evolving nature with time and the survival rate. The agents are evolved to ensure optimal ratio between unique and repetitive DNA sequences.