The analogy suggested in this title is also mentioned in the book's chapter on game theory, where the author said that game theory is just an extension of decision theories,
How does profit / utility maximization and cost /expanse minimization genuinely become different, while appearing to be much the same? If I am faced with some decisions about how much production to make, or how much to consume (which is slightly different since utility is not generally considered measurable as in production), I can generally adjust my input amount accordingly, and the important decision is not so much on choosing the cheapest ones (although should be adjusted for), but rather finding the satiating level, before which spending more can actually bring more profits, and the actual level is determined by a kind of efficiency of production technology (or greediness in consuming). Yet if I am trying to choose between alternative inputs for production so that cost is minimized, the relative efficiencies of respective inputs (efficiency of efficiencies / substitution rate) seem to become more relevant than their aggregated efficiency, and the gaming tinge (level of satiating) is not yet there. In a sense cost minimization is more conservative than profit maximization, and while profit maximizers generally do minimize cost, they can also make profits being luxurious. The traditional (or obsolete?) profit seekers either emphasize too much on minimizing cost or they believe that the more production the better (which could be that they don't really have alternative ways to produce, for example a field tending farmer, as opposed to a modern investor). Maybe that's how we accumulated enough for the modern consumers to think exactly the opposite, and since utilities are not really measurable, they just take them as unlimited.
The satiating level mentioned above should be present at all levels of optimization, and actually is very likely to be the one thing that links the simple (optimization) and complex (game) decision theories. At an optimal / equilibrium decision, any unilateral move away from the decision would lead astray the optimum. In applying the game theory, it is fitting this equilibrium concept into a specific setting, what kind of moves that can lead you astray, is it jumping upwards or swaying sideways that take you off the balance beam, that is to be found out, and theory just gives a criteria for you to judge whether you are right or not. In applying optimization theories and deciding for optimal actions however, these game settings are already part of how people found the theory, and it is already confirmed that swaying sideways can take you down from the balance beam, so you start from this point and find some other signs that can tell you whether you are swaying sideways or not, or more precisely, whether you are standing straight, touching the beam, or not, which is more or less equivalent statements / properties / definitions of swaying sideways, and in mathematical terms they are along the necessary and sufficient line of derivation, including equations.
Some common types of such signs of equilibrium / optimum.
(1) Tangency conditions. P27. P42. P51. P73. P89. P101. P107. P109. P110. (application diagrams not included)
Marginal rates of the decision factors that prevail at optimums is connected to some external factors such as price.
....a generalization of standard, one-person decision theory...
In a sense, the optimization part (of profit, cost on the firm's side and of utility, demand on the consumer's side) of Microeconomics is just about obtaining the payoff tables in games, and they constitute a subgame where only one agent is involved, i.e. subgames (improper) with only the terminal nodes in an extensive form game tree. And the same idea of an equilibrium found by state-wise examination (living in heaven without knowing the path to it) is probably also present in the less 'gamely' equilibrium analysis, where the strategy-payoff connection is the more complicated part to calculate, while in game theory such calculation is assumed to have already been informed for the various players but the strategy-strategy connection is more investigated to deal with complications in such ways.
How does profit / utility maximization and cost /expanse minimization genuinely become different, while appearing to be much the same? If I am faced with some decisions about how much production to make, or how much to consume (which is slightly different since utility is not generally considered measurable as in production), I can generally adjust my input amount accordingly, and the important decision is not so much on choosing the cheapest ones (although should be adjusted for), but rather finding the satiating level, before which spending more can actually bring more profits, and the actual level is determined by a kind of efficiency of production technology (or greediness in consuming). Yet if I am trying to choose between alternative inputs for production so that cost is minimized, the relative efficiencies of respective inputs (efficiency of efficiencies / substitution rate) seem to become more relevant than their aggregated efficiency, and the gaming tinge (level of satiating) is not yet there. In a sense cost minimization is more conservative than profit maximization, and while profit maximizers generally do minimize cost, they can also make profits being luxurious. The traditional (or obsolete?) profit seekers either emphasize too much on minimizing cost or they believe that the more production the better (which could be that they don't really have alternative ways to produce, for example a field tending farmer, as opposed to a modern investor). Maybe that's how we accumulated enough for the modern consumers to think exactly the opposite, and since utilities are not really measurable, they just take them as unlimited.
The satiating level mentioned above should be present at all levels of optimization, and actually is very likely to be the one thing that links the simple (optimization) and complex (game) decision theories. At an optimal / equilibrium decision, any unilateral move away from the decision would lead astray the optimum. In applying the game theory, it is fitting this equilibrium concept into a specific setting, what kind of moves that can lead you astray, is it jumping upwards or swaying sideways that take you off the balance beam, that is to be found out, and theory just gives a criteria for you to judge whether you are right or not. In applying optimization theories and deciding for optimal actions however, these game settings are already part of how people found the theory, and it is already confirmed that swaying sideways can take you down from the balance beam, so you start from this point and find some other signs that can tell you whether you are swaying sideways or not, or more precisely, whether you are standing straight, touching the beam, or not, which is more or less equivalent statements / properties / definitions of swaying sideways, and in mathematical terms they are along the necessary and sufficient line of derivation, including equations.
Some common types of such signs of equilibrium / optimum.
(it might be actually understood as a kind of order-preserving transformation from different equilibrium states to different values of a certain property)
(1) Tangency conditions. P27. P42. P51. P73. P89. P101. P107. P109. P110. (application diagrams not included)
Marginal rates of the decision factors that prevail at optimums is connected to some external factors such as price.
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