What We've Learned from NKS Chapter 3: The World of Simple Programs

In this episode of "What We've Learned from NKS", Stephen Wolfram is counting down to the 20th anniversary of A New Kind of Science with [another] chapter retrospective. If you'd like to contribute to the discussion in future episodes, you can participate through this YouTube channel or through the official Twitch channel of Stephen Wolfram here:   / stephen_wolfram  

Read all of NKS here: https://www.wolframscience.com/nks/

00:00 Start stream
0:38 SW goes live
1:05 Introduction of Chapter 3: Section 1
5:30 Section 2: More Cellular Automata (How does it relate to Chapter 2?)
38:08 Section 3: Mobile Automata
45:43 Section 4: Turing Machines
55:58 Section 5: Substitution Systems
1:06:17 Section 6: Sequential Substitution Systems
1:10:00 Section 7: Tag Systems
1:12:35 Section 8: Cyclic Tag Systems
1:15:48 Section 9: Register Machines
1:21:01 Section 10: Symbolic Systems
1:26:46 Conclusion of Chapter 3
1:30:24 In page 57, you mention that the maximum speed of a CA motion is one cell per step (although rules like 3 and 103 have an average speed of half a cell per step). How does this work? What does it mean for the speed to be one cell (or half a cell) per step?
1:31:33 ​stephen have you tried your rules in the von neumamm neighborhood?
1:32:06 possible combinations producing 2 possible outcomes giving 2^8 = 256 combinations. What happens with more combinations, such as 5 neighbors instead of 3?
1:33:06 ​Is there anything to learn about base 10 by looking at base 10 C.A.'s? I know there are a few examples later in the book but not much
1:34:21 In chemistry there is often hexagon patterns, could this be applied to hexagonal patterns to see if it generates patterns like say, DNA? So it would be cellular automata based on nearest neighbors of hexagons.
1:34:54 ​Are there biological analogies or analogs to mobile cellular automata?
1:35:31 are there universal mobile automatons such as universal turing machines? And are there something that can be mobile automata-equivalent like turing machine equivalence?
1:36:38 ​Does NKS suggest that P != NP is true but unprovable in Zermelo-Fraenkel set theory?
1:37:47 Is there a way to Determine if a Universally computable Cellular automaton is a Turing Tarpit or not?
1:40:25 ​How did you decide the order of the possible neighborhoods for elementary CA's with regards to how they are named encoded in binary
1:41:40 Does the simplest universal system for each type define a "translation distance" between each language?
1:42:14 how much study has there been with cellular automata in the brickwall neighbourhood?
1:42:43 ​Could you explain what your interpretation of what computational boundedness looks like for a biological system? For instance, how do you think it effects different organisms physically?

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