Previous Work

Information-Theoretic Analysis of ECA Rules (Genealogy Interceded Phenotypic Analysis (GIPA) of ECA rules)
R Goyal


Abstract.   This project demonstrated the grouping of the ECA Rules using information theoretic measures in light of Wolfram's classification of ECA, with 88 rule equivalence classes. This study used the concept of BiEntropy to compute the approximate information content of a binary string while quantifying the evolution of the macroscopic behavior in space-time diagrams for different rules. The amount of information processed by a CA rule in a space-time patch was captured through four proposed measures, i.e., DiffEntropy (DE), SimConfig Ordered (SCO), SimConfigImmediate (SCI), and SimConfigFluctuation (SCF). Based on the information-theoretic analysis, which was followed by the clustering of entropy values of different configurations through dynamic time warping (DTW), a Genealogy Interceded Phenotypic Analysis (GIPA) of 88 ECA rules was proposed.

Cellular Automata as models in Social Sciences
Rezki Chemlal


Abstract.   In this project we were interested in the use of 2 dimension cellular automata in social sciences , we were very flexible in the last point as we also inculed models in urban modeling.We also did not restict ourselevs to the formal definition of cellular automata as we considered also interesting models that may be considered close to cellular automata. We realised programs for all models.

Modeling the Spread of Covid-19 with 2-D Cellular Automata
Subrata Paul
Mentor: Kamalika Bhattacharjee

Abstract.   This project focuses on developing a model that can accurately simulate COVID-19's global dissemination patterns. We utilize cellular automaton (CA) to build such a model. In this project, a new variant of CA called Temporary Stochastic Cellular Automata (TSCA) is used, where two rules is being utilized, one of which serves as a default rule and the other of which is a probabilistic rule that is applied with some probability. To consider the mutation of the COVID-19 rule, we employ a set of TSCAs. Each TSCA is considered as (f, g)[τ] and at a time the applied TSCA is chosen from the set. The model evolves using two TSCA rules f and g, where f is represented as the propagation of the virus, g is represented as recovery function and g is applied with probability τ . The model is validated on the basis of a real-time dataset of spreading Coronavirus (SARS-COVID-19) over the world. This proposed model depicts the spreading scenario of the novel Coronavirus which has caused a global pandemic.

Isomorphism In Cellular Automata
Vicky Vikrant
Mentor: Sukanya Mukherjee

Abstract.   This work focuses on the isomorphism of cellular automata (CAs). Two cellular automata are said to be isomorphic if their configurations evolve in the similar way. As a model, here we use non-uniform elementary cellular automata under null boundary and discover few inherent properties of CAs to decide whether the given cellular automata are isomorphic.

Hexagonal Cellular Automata Simulation of Intergranular Cracking in Polycrystalline Materials
Tarun Kumaar M K, Deeraj H, and Suvetha M
Mentor: Prince Gideon Kubendran Amos

Abstract.   The model takes an input of the desired number of nuclei, which are then distributed at random throughout the domain. For this system, we are considering 18 different grain orientations associated with their own unique colours. Conventionally, cellular automata are associated with square discretization but here we have implemented hexagonal discretization and attempt to undertake a qualitative comparison between them.