Tangram & Polyform Pro vs Genetic Algorithms

1. About Tangram & Polyform Tangram is China's most famous puzzle game. In the early nineteenth century tangram became the first international puzzle. There are many tangram style puzzle games in the world. Polyform is a plane figure constructed by joining together identical basic polygons. The basic polygon is often a regular polygon, such as a square or a triangle. 2. About This Game This game contains twelve types of tangram puzzles and six types polyform puzzles. Games and levels are constantly added. Tangram puzzles include the Chinese classic Tangram 15 pieces puzzle(Yi Zhi Tu) and Modern Tangram, as well as T puzzle, Heart-shaped puzzle, Pythagoras, Sphinx, Columbus' egg and Kreuzspiel. Polyform puzzles include Polystick, Polyiammond, Polyomino, Polyhex, Polyabolo and Polybrick. There are three kind of play methods. Not just move. You can play classic game(Move, Flip & Rotate) or for relaxing(Just Move). Features: A. 12 types of Tangram puzzles and 6 types of Polyform puzzles. B. Three Play Methods. C. Over 4000 Levels and Will Add More. D. Easy to Play. E. Five Themes. 3. How to Play A. This game have Three Play Methods. Just Move. Move & Flip. Move, Flip & Rotate. B. Move: Touch the Piece and move. Flip: Click the Piece. Rotate:Long touch the Piece. C. Get Hint: Click the Hint Button. Each Level has 2 hints.

Genetic algorithms are one of the search and optimisation methods. The aim of optimisation is to increase efficiency in reaching a certain optimal value. Genetic algorithms are based on the mechanisms of natural selection and heredity. The basic genetic algorithm is built from three operations: reproduction, crossing, and mutation. Genetic algorithms operate on populations of coding sequences and use random selection rules to search for the global optimal value. However, these random rules are defined to give the appropriate direction of the search (through various selection mechanisms or scaling of fitness functions). This basic procedure is enhanced by certain genetic manipulations, such as those seen in nature. They include the mechanisms of dominance, diploidy, inversion, and other reconfiguration mechanisms that occur at the chromosome level. Users can design textual or graphical scaling patterns for the fitness function and then use them in simulations. The application also provides a preliminary analysis of statistical data concerning the distribution of the fitness function in the population. The program allows the user to compare non-random procedures (e.g. scaling of fitness functions) by using the same pseudorandom sequence (for procedures requiring randomization, such as selection, etc.) in successive simulations. In order to better visualize the genetic processes taking place during the simulation, some of them are presented to the user using animations. Additionally, some of the data obtained from simulations can be saved and shared.