What’s remarkable about this sort of repetitive, self-organising behaviour is that it’s contrary to how the Universe usually behaves. Everything should actually get more random, dispersed and chaotic as time marches on. That’s the second law of thermodynamics – everything tends towards chaos, and entropy generally increases. So what’s going on?
Complex systems are self-organising because they possess attractors.These are cycles of mutually reinforcing states that allow processes to achieve apoint of stability, not by losing energy until they stop, but through what’s known as dynamic equilibrium. An intuitive example is homeostasis. If you’re startled by a predator, your heartbeat and breathing will speed up, but you’ll automatically do something to restore your cardiovascular system to a calmer state (following the so-called ‘fight or flight’ response). Any time there’s a deviation from the attractor, this triggers flows of thoughts, feelings and movements that eventually take you back to your cycle of attracting, familiar states. In humans, all the excitations of our body and brain can be described as moving towards our attractors, that is, towards our most probable states.
With every new experience, your organism engages in inference to fit what’s happening into a familiar pattern
You’d hardly consider the process of evolution or natural selection in terms of inference – or would you? In fact, that’s exactly the interpretation currently found in theoretical neurobiology. It turns out, for example, that the way nature ‘selects’ organisms for their capacity to survive and reproduce is based on inference. Take a population of crabs as the system in question, and the aggregated features or phenotypes of its individuals as its ‘state’. These crabs can have claws of different sizes, shells that are harder or softer, and eyes that see better above water or below. Such diverse phenotypes amount to multiple hypotheses about what might ‘work’; each individual is a hypothesis or model of what should occupy this ecological niche, and must compete for selection under pressure from the environment.
Complex systems are self-organising because they possess attractors.These are cycles of mutually reinforcing states that allow processes to achieve apoint of stability, not by losing energy until they stop, but through what’s known as dynamic equilibrium. An intuitive example is homeostasis. If you’re startled by a predator, your heartbeat and breathing will speed up, but you’ll automatically do something to restore your cardiovascular system to a calmer state (following the so-called ‘fight or flight’ response). Any time there’s a deviation from the attractor, this triggers flows of thoughts, feelings and movements that eventually take you back to your cycle of attracting, familiar states. In humans, all the excitations of our body and brain can be described as moving towards our attractors, that is, towards our most probable states.
With every new experience, your organism engages in inference to fit what’s happening into a familiar pattern
You’d hardly consider the process of evolution or natural selection in terms of inference – or would you? In fact, that’s exactly the interpretation currently found in theoretical neurobiology. It turns out, for example, that the way nature ‘selects’ organisms for their capacity to survive and reproduce is based on inference. Take a population of crabs as the system in question, and the aggregated features or phenotypes of its individuals as its ‘state’. These crabs can have claws of different sizes, shells that are harder or softer, and eyes that see better above water or below. Such diverse phenotypes amount to multiple hypotheses about what might ‘work’; each individual is a hypothesis or model of what should occupy this ecological niche, and must compete for selection under pressure from the environment.
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