Topics: Game theory, Economics, Profit maximization Pages: 2 (418 words) Published: July 7, 2012
Emar M. AgustinOpeRsea
BSIT 501 July 6, 2012

I. Maximax
A strategy or algorithm that seeks to maximize the maximum possible result (that is, that prefers the alternative with the chance of the best possible outcome, even if it’s expected outcome and its worst possible outcome are worse than other alternatives); often used attributively, as "maximax strategy", "maximax approach", and so on.

II. Maximin
It suggests that the decision-maker should choose the alternative which maximises the minimum payoff he can get. This pessimistic approach implies that the decision-maker should expect the worst to happen.

III. Minimax
A rule used in decision theory, game theory, statistics and philosophy for minimizing the possible loss for a worst case (maximum loss) scenario. Alternatively, it can be thought of as maximizing the minimum gain (maximin). Originally formulated for two-player zero-sum game theory, covering both the cases where players take alternate moves and those where they make simultaneous moves, it has also been extended to more complex games and to general decision making in the presence of uncertainty.

IV. Laplace Criteria
If the probabilities of several chance events are unknown, they should be assumed equal, and the different actions should be judged according to their payoffs averaged over all the states of nature.

V. Criterion of Realism
Often called weighted average, the criterion of realism (or Hurwicz) decision criterion is a compromise between optimistic and a pessimistic decision.

VI. Marginal Analysis
The process of identifying the benefits and costs of different alternatives by examining the incremental effect on total revenue and total cost caused by a very small (just one unit) change in the output or input of each alternative. Marginal analysis supports decision-making based on marginal or incremental changes to resources instead of one based on totals or averages.

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