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In this video I cover 2 papers:
1) NEAT: NeuroEvolution of Augmenting Topologies - a seminal paper from 2002 that evolves not just the network weights but also network architectures
2) CPPN: Compositional Pattern Producing Networks:
A Novel Abstraction of Development - an interesting model of developmental biology with a completely different approach compared to e.g. cellular automata models
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✅ NEAT paper: http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf
✅ CPPN paper: http://eplex.cs.ucf.edu/papers/stanley_gpem07.pdf
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⌚️ Timetable:
00:00 Intro to NEAT and CPPNs
02:35 Basic ideas behind NEAT
07:55 NEAT genome explained
11:05 Competing conventions problem
13:25 NEAT mutations explained
15:30 NEAT genome mating explained
19:20 Maintaining innovations via speciation
25:25 Explicit fitness sharing
29:45 NEAT on XOR task
31:30 CPPNs and neural automata
36:40 Spatial signal as a chemical gradient abstraction
39:20 Composing functions
45:10 CPPN main idea recap
46:45 Breeding "images" using CPPNs
49:20 CPPNs are highly expressive (symmetries, repetition...)
54:17 HyperNEAT idea explained
57:43 Outro
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#NEAT #CPPN #evolution