Complicated system

The JC’s amateur guide to systems theory™ →Go uptown Complicated systems require interaction with autonomous agents whose specific behaviour is beyond the observer’s control, and might be intended to defeat the observer’s objective, but whose range of behaviour is deterministic, rule-bound and known and can be predicted in advance, and where the observer’s observing behaviour does not itself interfere with the essential equilibrium of the system. You know you have a complicated system when it cleaves to a comprehensive set of axioms and rules, and thus it is a matter of making sure that the proper models are being used for the situation at hand. Chess and Alpha Go are complicated, but not complex, systems. So are most sports. You can “force-solve” them, at least in theory. Complicated systems benefit from skilled management and some expertise to operate: a good chess player will do better than a poor one, and clearly a skilled, fit footballer can execute a plan better than a wheezy novice — but in the right hands and given good instructions even a mediocre player can usually manage without catastrophe. While success will be partly a function of user’s skill and expertise, a bad player with a good plan may defeat a skilled player with a bad one. Given enough processing power, complicated systems are predictable, determinative and calculable. They’re tame, not wicked problems. Index: Click ᐅ to expand: Systems theory The Devil’s Advocate Tell me more Sign up for our newsletter — or just get in touch: for ½ a weekly 🍺 you get to consult JC. Ask about it here.

Zero-sum games, when one player wins and one loses, are generally complicated systems, even though practically solving them may be extremely hard, and (like Chess and Go) they may not yet have been solved. Hence there is room for expertise to make a difference: if part of the system is a player just like you, only intent in getting the opposite outcome, then who wins will be a determined by who most skilfully uses the rules of the game to her advantage. A chess grandmaster will do better against IBM’s Dr Watson than will a novice, though there is always the chance you’ll play so badly that all the wiseguy’s sophisticated strategies fail and you walk her into an accidental checkmate when all you were trying to do is line your prawns and your horseys up because they looked nice that way. In a simple system, an expert has little advantage over a novice will a set of instructions.

Artificial intelligence and computing power is pretty good at handling complicated systems.