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Simulation of a Cellular Automaton with Markov Chains: Applications in Self-Organized Dynamical Systems

over the past years, technology has allowed information technology to contemplate complex events as well as complex semantic features to predict what types of "thoughts" are being conceptualized. The introduction of the neuro-robotics field allows a mix of different disciplines to inter-collate and produce actual results that could be considered outputs of a science-fiction novel 20 twenty years ago. In the present work, we attempted to present an example of how an automaton can move in an environment with obstacles, by regulating its behavior so as to allow a decision based on rewards and penalties. Examples of the robotic behavior, running on a virtual environment are presented, along with a discussion of its different possibilities expressed as a penalty function for the behavior of the robot.