title
7.3: The Game of Life - The Nature of Code

description
This video covers the Game of Life 2D cellular automaton in Processing (Java). Read along: http://natureofcode.com/book/chapter-7-cellular-automata/#chapter07_section6 Original 1970 Scientific American Article: http://www.ibiblio.org/lifepatterns/october1970.html Code: https://github.com/shiffman/The-Nature-of-Code-Examples Steve Klise's GOL processing.js implementation: https://github.com/stevenklise/ConwaysGameOfLife Exploring Emergence: http://llk.media.mit.edu/projects/emergence/ Help us caption & translate this video! http://amara.org/v/Qbva/ 📄 Code of Conduct: https://github.com/CodingTrain/Code-of-Conduct

detail
{'title': '7.3: The Game of Life - The Nature of Code', 'heatmap': [{'end': 499.216, 'start': 481.212, 'weight': 0.703}, {'end': 534.216, 'start': 499.236, 'weight': 0.891}, {'end': 578.787, 'start': 551.45, 'weight': 0.7}, {'end': 609.082, 'start': 587.933, 'weight': 0.954}, {'end': 668.614, 'start': 646.119, 'weight': 0.786}], 'summary': "Explores the game of life cellular automaton, based on john conway's principles, with simple rules leading to complex growth patterns. it delves into its mechanics, principles, and the use of two-dimensional arrays in programming for simulation, emphasizing emergent behaviors and potential applications in image processing.", 'chapters': [{'end': 132.253, 'segs': [{'end': 33.324, 'src': 'embed', 'start': 2.799, 'weight': 0, 'content': [{'end': 6.401, 'text': "Now we're ready to talk about a two-dimensional cellular automaton.", 'start': 2.799, 'duration': 3.602}, {'end': 11.544, 'text': "And the one we're going to look at is arguably the most famous cellular automaton of all, the game of life.", 'start': 6.461, 'duration': 5.083}, {'end': 14.466, 'text': 'So in 1970, I encourage you all to read this article.', 'start': 11.664, 'duration': 2.802}, {'end': 22.491, 'text': "Martin Gardner published an article in Scientific American called Mathematical Games the Fantastic Combinations of John Conway's New Solitaire Game Life.", 'start': 14.886, 'duration': 7.605}, {'end': 26.535, 'text': 'This was really a thought experiment in many ways.', 'start': 24.332, 'duration': 2.203}, {'end': 27.536, 'text': 'Get out your checkerboard.', 'start': 26.595, 'duration': 0.941}, {'end': 28.538, 'text': 'Get out your checkers.', 'start': 27.577, 'duration': 0.961}, {'end': 33.324, 'text': 'A checker on a cell means one.', 'start': 29.099, 'duration': 4.225}], 'summary': 'Discussion of the famous 2d cellular automaton, the game of life, highlighted in a 1970 scientific american article by martin gardner.', 'duration': 30.525, 'max_score': 2.799, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc2799.jpg'}, {'end': 87.303, 'src': 'embed', 'start': 48.176, 'weight': 1, 'content': [{'end': 54.739, 'text': 'And could a system that exhibits the properties of biological reproduction be simulated with such simple rules in a game-like way?', 'start': 48.176, 'duration': 6.563}, {'end': 59.34, 'text': 'And so Conway started with a few core principles, which are outlined nicely in this article.', 'start': 55.079, 'duration': 4.261}, {'end': 64.762, 'text': 'There should be no initial pattern for which there is a simple proof that the population can grow without limit.', 'start': 59.86, 'duration': 4.902}, {'end': 69.506, 'text': 'There should be initial patterns, however, that apparently do grow out without limit.', 'start': 65.322, 'duration': 4.184}, {'end': 78.314, 'text': "So in other words, this system can kind of grow out of control, but there's no way to predict or prove exactly how it's going to behave,", 'start': 69.826, 'duration': 8.488}, {'end': 79.556, 'text': 'just from its initial pattern.', 'start': 78.314, 'duration': 1.242}, {'end': 87.303, 'text': "And if you think about that, that's really Wolfram's, from the previous video, that's really Wolfram's classification for complexity.", 'start': 79.836, 'duration': 7.467}], 'summary': "Conway's system exhibits biological reproduction with simple rules, demonstrating unpredictable complexity.", 'duration': 39.127, 'max_score': 48.176, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc48176.jpg'}], 'start': 2.799, 'title': 'The game of life cellular automaton', 'summary': "Introduces the famous game of life, a cellular automaton with simple rules leading to complex growth patterns, based on john conway's principles.", 'chapters': [{'end': 132.253, 'start': 2.799, 'title': 'The game of life cellular automaton', 'summary': "Introduces the famous game of life, a cellular automaton in which simple rules lead to complex and unpredictable growth patterns, settling into stable configurations or oscillating phases, as outlined by john conway's core principles.", 'duration': 129.454, 'highlights': ["John Conway published the famous cellular automaton 'The Game of Life' in 1970, aiming to simulate biological reproduction with simple rules.", "The game exhibits unpredictable growth patterns and settles into stable configurations or oscillating phases, aligning with Wolfram's classification for complexity.", 'The core principles of the game include no initial pattern for limitless population growth, initial patterns that grow without predictability, and simple initial patterns that change before settling into stable, uniform, or oscillating states.']}], 'duration': 129.454, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc2799.jpg', 'highlights': ["John Conway published 'The Game of Life' in 1970 to simulate biological reproduction.", "The game exhibits unpredictable growth patterns and aligns with Wolfram's complexity classification.", 'The core principles include no initial pattern for limitless population growth and simple patterns settling into stable states.']}, {'end': 471.585, 'segs': [{'end': 182.168, 'src': 'embed', 'start': 132.353, 'weight': 0, 'content': [{'end': 140.879, 'text': "Can we achieve this, again, just with Squares on a grid, and each square, which we're calling a cell, has a 0 or a 1.", 'start': 132.353, 'duration': 8.526}, {'end': 147.364, 'text': "So let's look at how we might define this from a systems point of view, and then ultimately how we would write the code to simulate this.", 'start': 140.879, 'duration': 6.485}, {'end': 153.208, 'text': 'And I should note, Conway was doing this not only without processing, but without a computer, essentially.', 'start': 147.424, 'duration': 5.784}, {'end': 156.07, 'text': "Okay, so let's come over here.", 'start': 153.348, 'duration': 2.722}, {'end': 164.616, 'text': 'So one of the things you remember from the one-dimensional CA and this is kind of one of the reasons why we looked at it in this order is that if we have this cell,', 'start': 156.09, 'duration': 8.526}, {'end': 165.836, 'text': "here is the cell's neighborhood.", 'start': 164.616, 'duration': 1.22}, {'end': 167.558, 'text': "It's just three cells.", 'start': 166.237, 'duration': 1.321}, {'end': 172.081, 'text': 'Myself, the friend to the right, and the friend to the left.', 'start': 168.298, 'duration': 3.783}, {'end': 175.063, 'text': 'Now, in a two-dimensional CA.', 'start': 172.641, 'duration': 2.422}, {'end': 182.168, 'text': 'We have something a little bit more complex going on.', 'start': 179.226, 'duration': 2.942}], 'summary': "Conway's game of life simulates cells on a grid with 0s and 1s, exploring one and two-dimensional cellular automata.", 'duration': 49.815, 'max_score': 132.353, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc132353.jpg'}, {'end': 319.285, 'src': 'embed', 'start': 282.955, 'weight': 2, 'content': [{'end': 285.557, 'text': 'So we have three key principles in the game of life.', 'start': 282.955, 'duration': 2.602}, {'end': 294.505, 'text': "Death, birth, and what we'll call stasis, I guess.", 'start': 287.659, 'duration': 6.846}, {'end': 304.333, 'text': 'So death means we are a cell and our state was one, but in the next generation, our state is going to be a zero, not a six.', 'start': 296.287, 'duration': 8.046}, {'end': 311.858, 'text': 'When do we die? We die from two possible principles.', 'start': 305.813, 'duration': 6.045}, {'end': 313.8, 'text': 'One is overpopulation.', 'start': 312.359, 'duration': 1.441}, {'end': 315.481, 'text': 'We are crowded.', 'start': 314.421, 'duration': 1.06}, {'end': 318.584, 'text': "I don't like lots of cells with a state of one around me.", 'start': 315.581, 'duration': 3.003}, {'end': 319.285, 'text': "It's too much.", 'start': 318.664, 'duration': 0.621}], 'summary': 'The game of life involves death, birth, and stasis, with overpopulation causing death.', 'duration': 36.33, 'max_score': 282.955, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc282955.jpg'}, {'end': 403.642, 'src': 'embed', 'start': 374.122, 'weight': 4, 'content': [{'end': 376.745, 'text': "We're going to go from dead, zero, to alive.", 'start': 374.122, 'duration': 2.623}, {'end': 385.494, 'text': 'The only time we have birth is if we have exactly three live neighbors.', 'start': 377.325, 'duration': 8.169}, {'end': 389.168, 'text': 'Exactly three live neighbors.', 'start': 387.466, 'duration': 1.702}, {'end': 393.092, 'text': 'So these are the conditions by which we die, go from 1 to 0.', 'start': 389.488, 'duration': 3.604}, {'end': 395.574, 'text': 'This is the condition by which we go from 0 to 1.', 'start': 393.092, 'duration': 2.482}, {'end': 397.856, 'text': 'And I said the last principle here is stasis.', 'start': 395.574, 'duration': 2.282}, {'end': 403.642, 'text': "In essence, what we're saying is in all other cases, state remains the same.", 'start': 398.377, 'duration': 5.265}], 'summary': 'Cell transitions based on live neighbor count and stasis principle.', 'duration': 29.52, 'max_score': 374.122, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc374122.jpg'}], 'start': 132.353, 'title': "Conway's game of life and its principles", 'summary': "Delves into the principles and mechanics of conway's game of life, a two-dimensional cellular automata with 512 configurations and a neighborhood of 9 cells, exploring the concepts of death, birth, stasis, and the influence of live neighbors on state transitions, leading to emergent behaviors similar to bacterial reproduction.", 'chapters': [{'end': 241.099, 'start': 132.353, 'title': "Conway's game of life", 'summary': "Discusses the two-dimensional cellular automata, specifically conway's game of life, which involves a grid with cells containing a 0 or 1, with a total of 512 possible configurations and a neighborhood of 9 cells, guiding the simulation process.", 'duration': 108.746, 'highlights': ["Conway's Game of Life involves a grid with cells containing a 0 or 1, with a total of 512 possible configurations.", 'The neighborhood of a cell in two-dimensional CA consists of nine cells, including those to the right, left, up, down, and diagonally.']}, {'end': 471.585, 'start': 241.439, 'title': 'The game of life', 'summary': 'Discusses the principles of the game of life, including death, birth, and stasis, with rules for transitioning between states based on the number of live neighbors, leading to complex outcomes like bacterial reproductive behaviors.', 'duration': 230.146, 'highlights': ['The Game of Life involves three key principles: death, birth, and stasis, with specific conditions for transitioning between states based on the number of live neighbors, resulting in complex and varied outcomes. The Game of Life involves principles of death, birth, and stasis, with specific conditions for transitioning between states based on the number of live neighbors, leading to complex and varied outcomes.', "The principle of death is determined by overpopulation (four or more live cells surrounding a cell) or loneliness (one or fewer live neighbors), leading to the cell's state transitioning from 1 to 0. The principle of death is determined by overpopulation (four or more live cells surrounding a cell) or loneliness (one or fewer live neighbors), leading to the cell's state transitioning from 1 to 0.", "The principle of birth occurs when a cell transitions from 0 to 1, only if it has exactly three live neighbors, showcasing the specific conditions for the cell's state transition. The principle of birth occurs when a cell transitions from 0 to 1, only if it has exactly three live neighbors, showcasing the specific conditions for the cell's state transition."]}], 'duration': 339.232, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc132353.jpg', 'highlights': ["Conway's Game of Life involves a grid with cells containing a 0 or 1, with a total of 512 possible configurations.", 'The neighborhood of a cell in two-dimensional CA consists of nine cells, including those to the right, left, up, down, and diagonally.', 'The Game of Life involves three key principles: death, birth, and stasis, with specific conditions for transitioning between states based on the number of live neighbors, resulting in complex and varied outcomes.', "The principle of death is determined by overpopulation (four or more live cells surrounding a cell) or loneliness (one or fewer live neighbors), leading to the cell's state transitioning from 1 to 0.", "The principle of birth occurs when a cell transitions from 0 to 1, only if it has exactly three live neighbors, showcasing the specific conditions for the cell's state transition."]}, {'end': 706.681, 'segs': [{'end': 511.062, 'src': 'heatmap', 'start': 481.212, 'weight': 0.703, 'content': [{'end': 483.113, 'text': "OK So let's take a look at a couple things.", 'start': 481.212, 'duration': 1.901}, {'end': 488.317, 'text': 'Number one we should point out is that no longer do we have a one-dimensional array.', 'start': 483.374, 'duration': 4.943}, {'end': 493.154, 'text': 'We now have a two-dimensional array talking about RCA.', 'start': 489.672, 'duration': 3.482}, {'end': 499.216, 'text': 'RCA at a given generation is a two-dimensional grid of states, not a one-dimensional grid.', 'start': 493.474, 'duration': 5.742}, {'end': 501.297, 'text': 'So in this example, we have a two-dimensional array.', 'start': 499.236, 'duration': 2.061}, {'end': 508.601, 'text': 'And if you are not familiar with two-dimensional arrays, I will include a link to a tutorial on the processing website about two-dimensional arrays.', 'start': 501.758, 'duration': 6.843}, {'end': 511.062, 'text': 'Now, a couple other things.', 'start': 509.581, 'duration': 1.481}], 'summary': 'Two-dimensional arrays in rca offer more states, see tutorial for details.', 'duration': 29.85, 'max_score': 481.212, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc481212.jpg'}, {'end': 541.824, 'src': 'heatmap', 'start': 499.236, 'weight': 0, 'content': [{'end': 501.297, 'text': 'So in this example, we have a two-dimensional array.', 'start': 499.236, 'duration': 2.061}, {'end': 508.601, 'text': 'And if you are not familiar with two-dimensional arrays, I will include a link to a tutorial on the processing website about two-dimensional arrays.', 'start': 501.758, 'duration': 6.843}, {'end': 511.062, 'text': 'Now, a couple other things.', 'start': 509.581, 'duration': 1.481}, {'end': 517.485, 'text': 'We have the same idea here, where we have a function called generate.', 'start': 511.102, 'duration': 6.383}, {'end': 521.147, 'text': 'The function called generate is where we create the next generation.', 'start': 517.765, 'duration': 3.382}, {'end': 524.79, 'text': 'And we have to compute the states for every single next generation.', 'start': 521.428, 'duration': 3.362}, {'end': 534.216, 'text': 'Now what is the value that we need to calculate? Notice all of these rules require us to know the total number of live neighbors.', 'start': 524.83, 'duration': 9.386}, {'end': 536.878, 'text': 'We need to say, here am I.', 'start': 534.696, 'duration': 2.182}, {'end': 537.498, 'text': 'Look around me.', 'start': 536.878, 'duration': 0.62}, {'end': 539.96, 'text': 'At this moment in time, how many neighbors are alive?', 'start': 537.778, 'duration': 2.182}, {'end': 541.243, 'text': 'Are there four?', 'start': 540.663, 'duration': 0.58}, {'end': 541.824, 'text': 'Are there one?', 'start': 541.323, 'duration': 0.501}], 'summary': 'Explanation of two-dimensional arrays and calculation of live neighbors for next generation.', 'duration': 42.588, 'max_score': 499.236, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc499236.jpg'}, {'end': 578.787, 'src': 'heatmap', 'start': 551.45, 'weight': 0.7, 'content': [{'end': 559.955, 'text': "One thing that's a little bit insane here is we have this loop going through every single cell, a nested for loop for every column, for every row.", 'start': 551.45, 'duration': 8.505}, {'end': 563.397, 'text': "We're going to do this to every cell in our two-dimensional array.", 'start': 559.975, 'duration': 3.422}, {'end': 568.66, 'text': "Once we get to each cell, we've got to do a little mini loop.", 'start': 565.638, 'duration': 3.022}, {'end': 572.823, 'text': "This little mini loop is the loop that says hey, let's look at our own little neighborhood, right?", 'start': 568.9, 'duration': 3.923}, {'end': 573.723, 'text': 'What does that mean?', 'start': 573.043, 'duration': 0.68}, {'end': 578.787, 'text': "If we're looking at this particular cell, we're going to loop through all of these cells, right?", 'start': 574.124, 'duration': 4.663}], 'summary': 'Nested loops iterate through each cell in a two-dimensional array, creating a mini loop to analyze neighborhood cells.', 'duration': 27.337, 'max_score': 551.45, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc551450.jpg'}, {'end': 614.244, 'src': 'heatmap', 'start': 580.868, 'weight': 1, 'content': [{'end': 582.869, 'text': 'And when we get to each one, this one, we look at these.', 'start': 580.868, 'duration': 2.001}, {'end': 584.01, 'text': 'This one, we look at these.', 'start': 583.09, 'duration': 0.92}, {'end': 586.292, 'text': "And that's what this mini loop is right here.", 'start': 584.25, 'duration': 2.042}, {'end': 587.913, 'text': 'And what do we do? We add up.', 'start': 586.332, 'duration': 1.581}, {'end': 591.115, 'text': 'We start with a total number of neighbors at 0, and we add them all together.', 'start': 587.933, 'duration': 3.182}, {'end': 598.133, 'text': 'Once we know the total number of neighbors that are alive, We can then implement our rules.', 'start': 591.515, 'duration': 6.618}, {'end': 601.335, 'text': "And let's see if I can, ah, I'm not well prepared here.", 'start': 598.193, 'duration': 3.142}, {'end': 606.54, 'text': "I'm just going to make this much wider so you can see the awkward pause.", 'start': 601.355, 'duration': 5.185}, {'end': 609.082, 'text': 'Sing to yourself about the game of life.', 'start': 607.02, 'duration': 2.062}, {'end': 614.244, 'text': 'Okay, so if we look at this here, we can see here are those rules.', 'start': 611.582, 'duration': 2.662}], 'summary': 'Discussion about implementing rules for the game of life and totaling neighbors.', 'duration': 33.376, 'max_score': 580.868, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc580868.jpg'}, {'end': 676.101, 'src': 'heatmap', 'start': 646.119, 'weight': 0.786, 'content': [{'end': 649.801, 'text': 'And again, the next generation then becomes the current generation.', 'start': 646.119, 'duration': 3.682}, {'end': 655.141, 'text': "When we run this, You've all been waiting for this your whole life, the game of life.", 'start': 649.841, 'duration': 5.3}, {'end': 656.382, 'text': 'Here we go.', 'start': 655.862, 'duration': 0.52}, {'end': 657.603, 'text': 'Here is the result.', 'start': 656.723, 'duration': 0.88}, {'end': 660.286, 'text': "And we can see it's just going to go for quite some time.", 'start': 657.644, 'duration': 2.642}, {'end': 664.27, 'text': 'We can see there are these places where it reaches a static state.', 'start': 660.546, 'duration': 3.724}, {'end': 668.614, 'text': "There are these little oscillating places where it's oscillating back and forth, back and forth.", 'start': 664.61, 'duration': 4.004}, {'end': 671.937, 'text': "And I encourage you, if you're wondering why is it doing that?", 'start': 668.654, 'duration': 3.283}, {'end': 676.101, 'text': 'get out a piece of graph paper, get out a checkerboard and try to calculate the generation.', 'start': 671.937, 'duration': 4.164}], 'summary': 'Simulation results show static and oscillating states in the next generation.', 'duration': 29.982, 'max_score': 646.119, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc646119.jpg'}, {'end': 676.101, 'src': 'embed', 'start': 649.841, 'weight': 2, 'content': [{'end': 655.141, 'text': "When we run this, You've all been waiting for this your whole life, the game of life.", 'start': 649.841, 'duration': 5.3}, {'end': 656.382, 'text': 'Here we go.', 'start': 655.862, 'duration': 0.52}, {'end': 657.603, 'text': 'Here is the result.', 'start': 656.723, 'duration': 0.88}, {'end': 660.286, 'text': "And we can see it's just going to go for quite some time.", 'start': 657.644, 'duration': 2.642}, {'end': 664.27, 'text': 'We can see there are these places where it reaches a static state.', 'start': 660.546, 'duration': 3.724}, {'end': 668.614, 'text': "There are these little oscillating places where it's oscillating back and forth, back and forth.", 'start': 664.61, 'duration': 4.004}, {'end': 671.937, 'text': "And I encourage you, if you're wondering why is it doing that?", 'start': 668.654, 'duration': 3.283}, {'end': 676.101, 'text': 'get out a piece of graph paper, get out a checkerboard and try to calculate the generation.', 'start': 671.937, 'duration': 4.164}], 'summary': 'Simulation shows static states and oscillations, encouraging hands-on calculations.', 'duration': 26.26, 'max_score': 649.841, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc649841.jpg'}], 'start': 471.965, 'title': 'Two-dimensional arrays in programming and game of life simulation', 'summary': 'Discusses the concept of two-dimensional arrays in programming, emphasizing their use in rca as a two-dimensional grid of states and explains the process of creating the next generation in the game of life simulation, emphasizing the calculation of live neighbors, implementation of rules, and observation of resulting patterns over time.', 'chapters': [{'end': 517.485, 'start': 471.965, 'title': 'Two-dimensional arrays in programming', 'summary': 'Discusses the concept of two-dimensional arrays in programming, emphasizing their use in rca as a two-dimensional grid of states, and suggests exploring a tutorial on the processing website for further understanding.', 'duration': 45.52, 'highlights': ['The concept of two-dimensional arrays is emphasized, particularly in the context of RCA as a two-dimensional grid of states.', 'Suggestion to explore a tutorial on the processing website for further understanding of two-dimensional arrays.']}, {'end': 706.681, 'start': 517.765, 'title': 'Game of life simulation', 'summary': 'Explains the process of creating the next generation in the game of life simulation, emphasizing the calculation of live neighbors, implementation of rules, and observation of resulting patterns over time.', 'duration': 188.916, 'highlights': ['The function generate creates the next generation and computes states for every cell, involving the calculation of live neighbors and implementation of rules. The function generate is responsible for creating the next generation and computing states for every single cell, focusing on the calculation of live neighbors and implementing specific rules for different scenarios.', 'The process involves looping through every cell to assess the total number of live neighbors in the neighborhood. The process includes looping through every cell in a two-dimensional array to calculate the total number of live neighbors in the neighborhood.', 'The simulation results in static states as well as oscillations, prompting further analysis and observation of resulting patterns. The simulation results in static states and oscillations, leading to the need for further analysis and observation of the resulting patterns over time.']}], 'duration': 234.716, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc471965.jpg', 'highlights': ['The function generate computes states for every cell, involving live neighbors and rules.', 'The process includes looping through every cell to assess the total number of live neighbors.', 'The simulation results in static states and oscillations, prompting further analysis.']}, {'end': 963.128, 'segs': [{'end': 818.444, 'src': 'embed', 'start': 788.928, 'weight': 0, 'content': [{'end': 792.08, 'text': "But in my examples, I'm either ignoring the edge or doing wraparound.", 'start': 788.928, 'duration': 3.152}, {'end': 800.511, 'text': "The other thing I should just point out here and we're going to get to this in the next video is really how do we go a little further with this stuff?", 'start': 793.446, 'duration': 7.065}, {'end': 810.999, 'text': "Two obvious ways that you might think of as your own exercise and I'll talk about them a bit more in the next video is number one what's the thing that you're always looking at?", 'start': 801.012, 'duration': 9.987}, {'end': 818.444, 'text': "that you're working with, which is a two-dimensional grid of cells that have a state? Pixels.", 'start': 810.999, 'duration': 7.445}], 'summary': 'Exploring ways to manipulate a two-dimensional grid of cells, such as pixels.', 'duration': 29.516, 'max_score': 788.928, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc788928.jpg'}, {'end': 872.605, 'src': 'embed', 'start': 834.216, 'weight': 1, 'content': [{'end': 838.717, 'text': 'A blur is just saying, take a pixel and average it with its neighbors.', 'start': 834.216, 'duration': 4.501}, {'end': 845.839, 'text': "That's the rule for how a color changes from generation to generation if you were to apply a blur over and over again.", 'start': 838.917, 'duration': 6.922}, {'end': 853.161, 'text': "If you look in Photoshop, there's a convolution filter which allows you to set the weights of various pixels in a neighborhood.", 'start': 846.079, 'duration': 7.082}, {'end': 854.821, 'text': 'That is a CA algorithm.', 'start': 853.401, 'duration': 1.42}, {'end': 860.882, 'text': "I've seen water ripple-like effects, watercolor effects, all sorts of types of things that you could do with a CA.", 'start': 855.501, 'duration': 5.381}, {'end': 863.283, 'text': 'So one, you might think about applying this to image processing.', 'start': 860.922, 'duration': 2.361}, {'end': 872.605, 'text': 'The other thing you might think about, which I think is really important here, is the fact that these cells, they could be object-oriented.', 'start': 865.664, 'duration': 6.941}], 'summary': 'Ca algorithm applies blur to pixels, creating various effects, useful for image processing and object-oriented applications.', 'duration': 38.389, 'max_score': 834.216, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc834216.jpg'}], 'start': 707.522, 'title': '1d and 2d cellular automata', 'summary': 'Discusses handling edges in 1d cellular automata, presenting methods such as ignoring edges or implementing wraparound. it also explores the use of cellular automata in image processing, emphasizing pixel manipulation in a two-dimensional grid and the potential of object-oriented cells for enhanced functionalities.', 'chapters': [{'end': 810.999, 'start': 707.522, 'title': 'Handling edges in 1d cellular automata', 'summary': 'Discusses the considerations for handling edges in 1d cellular automata, demonstrating methods such as ignoring the edges or implementing wraparound, while also highlighting the potential challenges and trade-offs involved.', 'duration': 103.477, 'highlights': ["The edges are, in a sense, staying constant. We don't calculate their values. The method of starting at column 1 and ending at the total columns minus 1 allows for not calculating the values of the edges, simplifying the process.", "You could design different rules for the edges, but it's very inconvenient. Designing different rules for the edges is deemed as inconvenient and causing unnecessary trouble, discouraging this approach.", 'The chapter demonstrates methods of either ignoring the edge or implementing wraparound. The chapter showcases methods of handling edges, including ignoring them or implementing wraparound, providing practical examples of edge management.']}, {'end': 963.128, 'start': 810.999, 'title': 'Cellular automata in image processing', 'summary': 'Discusses the concept of cellular automata (ca) in image processing, highlighting how pixels in a two-dimensional grid can be manipulated to create various effects, and the potential of using object-oriented cells for enhanced functionalities.', 'duration': 152.129, 'highlights': ['Cellular automata (CA) algorithms are widely used in image processing, with techniques such as blurring involving averaging pixels with their neighbors. CA algorithms are commonly utilized in image processing, where techniques like blurring involve averaging pixels with their neighbors.', 'The potential of using object-oriented cells in place of two-dimensional integers for enhanced functionalities and possibilities in image processing. The concept of employing object-oriented cells instead of two-dimensional integers for expanded functionalities and possibilities in image processing is emphasized.', 'Exploration of various effects achievable through CA in image processing, such as water ripple-like effects and watercolor effects. The chapter explores the range of effects attainable through CA in image processing, including water ripple-like effects and watercolor effects.']}], 'duration': 255.606, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/tENSCEO-LEc/pics/tENSCEO-LEc707522.jpg', 'highlights': ['The chapter showcases methods of handling edges, including ignoring them or implementing wraparound, providing practical examples of edge management.', 'The concept of employing object-oriented cells instead of two-dimensional integers for expanded functionalities and possibilities in image processing is emphasized.', 'CA algorithms are commonly utilized in image processing, where techniques like blurring involve averaging pixels with their neighbors.']}], 'highlights': ['The Game of Life simulates biological reproduction and exhibits unpredictable growth patterns.', "Conway's Game of Life involves a grid with cells containing a 0 or 1, with a total of 512 possible configurations.", 'The neighborhood of a cell in two-dimensional CA consists of nine cells, including those to the right, left, up, down, and diagonally.', 'The Game of Life involves three key principles: death, birth, and stasis, with specific conditions for transitioning between states based on the number of live neighbors.', 'The function generate computes states for every cell, involving live neighbors and rules.', 'The chapter showcases methods of handling edges, including ignoring them or implementing wraparound, providing practical examples of edge management.', 'CA algorithms are commonly utilized in image processing, where techniques like blurring involve averaging pixels with their neighbors.']}