Antifragility in complex dynamical systems
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Re: Antifragility in complex dynamical systems
#2I've found that intentionally causing abrupt (but reasonable) changes to hyperparameters in evolutionary spiking neural network simulations (I.e between each generation) results in far more robust simulations that will meet fitness criteria with less likelihood of getting stuck somewhere. The tradeoff being that simulating will take longer, but this may be worth things like reducing the chances of your resource requirements going asymptotic half way through.
My current method of perturbation is to cap the total # of activations per candidate globally. When at least 3 improvements in the best global fitness score have been achieved, I cut the global activation limit in half. Obviously, this is fairly catastrophic for the current population. Each generation can increase the limit by 1% if no improvements made. This provides aggressive selection pressure for more efficient networks and forces a different kind of partial restart of the training process (I.e. do what you just did with 50% resources now). Very often this does result in optimization of the network. It also seems to make the networks rebound faster after restarts. At first, a restart can take 10-20 generations to recover. By generation 1000, this is closer to 1-2.
Re: Antifragility in complex dynamical systems
#3Is this just risk seeking behavior (in contrast to risk sensitive)
Re: Antifragility in complex dynamical systems
#4 Systems or organisms can be defined as antifragile if they derive benefit from systemic variability, volatility, randomness, or disorder.
Re: Antifragility in complex dynamical systems
#5I wish folks would write more plainly. “Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations.” Geish.
Re: Antifragility in complex dynamical systems
#6Systems or organisms can be defined as antifragile if they derive benefit from systemic variability, volatility, randomness, or disorder. If that's a riddle, death fits. Those things are characteristic of the pestilence, famine, war, etc. that feed death. The decay surrounding death is complex and dynamical. And death is more sustainable than any living system.
but death isn't a system or organism...
Re: Antifragility in complex dynamical systems
#7Systems or organisms can be defined as antifragile if they derive benefit from systemic variability, volatility, randomness, or disorder. If that's a riddle, death fits. Those things are characteristic of the pestilence, famine, war, etc. that feed death. The decay surrounding death is complex and dynamical. And death is more sustainable than any living system.
So life as a system benefits from the randomness — but inevitableness — of death, is how I interpret that. Benefits as in, key to its continual perpetuation.
Re: Antifragility in complex dynamical systems
#8I wish folks would write more plainly. “Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations.” Geish.
Well it is in a journal called "complexity." But I agree, that sentence is awful, I'm surprised they decided to lead with it, and nobody proof reading the paper objected.
Re: Antifragility in complex dynamical systems
#9Is this just risk seeking behavior (in contrast to risk sensitive)
Now I wonder what a machine learning model with risk seeking behaviour would look like.
Re: Antifragility in complex dynamical systems
#10I love how Taleb managed to translate an ideal from stoic philosophy into a precisely defined mathematical concept