Decision theory is only relevant in decisions that are difficult for some reason. A few types of decision have attracted particular attention: riskless choice between incommensurable commodities choice under uncertainty intertemporal choice social decisions Decision theory - Choice between incommensurable commodities. This area is concerned with the decision whether to have, say, one ton of guns and 3 tons of butter, or 2 tons of guns and 1 ton of butter. This ...

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Decision theory, Decision theory - Normative and descriptive decision theory, Decision theory - What kinds of decisions need a theory?, Decision theory - Choice between incommensurable commodities, Decision theory - Choice under uncertainty, Decision theory - Pascal's Wager, Decision theory - Alternatives to Probability, Decision theory - Intertemporal choice, Decision theory - Social decisions, Decision theory - Complex decisions, Decision theory - Paradox of choice

Read more here: » Decision theory: Encyclopedia II - Decision theory - What kinds of decisions need a theory?

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Decision theory, Decision theory - Normative and descriptive decision theory, Decision theory - What kinds of decisions need a theory?, Decision theory - Choice between incommensurable commodities, Decision theory - Choice under uncertainty, Decision theory - Pascal's Wager, Decision theory - Alternatives to Probability, Decision theory - Intertemporal choice, Decision theory - Social decisions, Decision theory - Complex decisions, Decision theory - Paradox of choice

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Under this theory, the dividend decision is very simple. The firm simply pays out, as dividends, any cash that is surplus after it invests in all available positive net present value projects. A key criticism of this theory is that it does not explain the observed dividend policies of real-world companies. Most companies pay relatively consistent dividends from one year to the next and managers tend to prefer to pay a steadily increasing dividend rather than paying a dividend that fluctuates dramatically from one year to the next. These criticisms have le ...

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The Dividend Decision, The Dividend Decision - The free cash flow theory of dividends, The Dividend Decision - Dividend clienteles, The Dividend Decision - Information signalling, The Dividend Decision - Conclusion

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Much of complexity theory deals with decision problems. A decision problem is a problem where the answer is always YES/NO. For example, the problem IS-PRIME is: given an integer written in binary, return whether it is a prime number or not. A decision problem is equivalent to a language, which is a set of finite-length strings. For a given decision problem, the equivalent language is the set of all strings for which the answer is YES. Decision problems are often considered because an arbitrary problem can always be reduc ...

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Computational complexity theory, Computational complexity theory - Overview, Computational complexity theory - Decision problems, Computational complexity theory - Complexity classes, Computational complexity theory - The P = NP question, Computational complexity theory - Intractability, Computational complexity theory - Notable researchers

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In classical statistical decision theory, we have an estimator δ that is used to estimate a parameter . We also assume a risk function R(θ,δ), usually specified as the integral of a loss function. In this framework, is called minimax if it satisfies . An alternative criterion in the decision theoretic framework is the Bayes estimator in the presence of a prior distribution Π. An esti ...

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Minimax, Minimax - Minimax criterion in statistical decision theory, Minimax - Minimax algorithm with alternate moves, Minimax - Minimax theorem with simultaneous moves, Minimax - Minimax in the face of uncertainty, Minimax - Minimax in non-zero-sum games, Minimax - External link

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In computer science, computational complexity theory is the branch of the theory of computation that studies the resources required during computation to solve a given problem. The most common resources are time (how many steps it takes to solve a problem) and space (how much memory it takes). Other resources can also be considered, such as how many parallel processors are needed to solve a problem in parallel. Complexity theory differs from the computability theory, which deals with whether a problem can be solved at al ...

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Computational complexity theory - Overview Computational complexity theory - Decision problems Computational complexity theory - Complexity classes Computational complexity theory - The P = NP question Computational complexity theory - Intractability Computational complexity theory - Notable researchers

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A particular pattern of dividend payments may suit one type of stock holder more than another. A retiree may prefer to invest in a firm that provides a consistently high dividend yield, whereas a person with a high income from employment may prefer to avoid dividends due to their high marginal tax rate on income. If clienteles exist for particular patterns of dividend payments, a firm may be able to maximise its stock price and minimise its cost of capital by catering to a particular clientele. This model may help to explain the relatively co ...

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The Dividend Decision, The Dividend Decision - The free cash flow theory of dividends, The Dividend Decision - Dividend clienteles, The Dividend Decision - Information signalling, The Dividend Decision - Conclusion

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A model developed by Merton Miller and Kevin Rock in 1985 suggests that dividend announcements convey information to investors regarding the firm's future prospects. Many earlier studies had shown that stock prices tend to increase when an increase in dividends is announced and tend to decrease when a decrease or omission is announced. Miller and Rock pointed out that this is likely due to the information content of dividends. When investors have incomplete information about the firm (perhaps due to opaque accounting practices) they w ...

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The Dividend Decision, The Dividend Decision - The free cash flow theory of dividends, The Dividend Decision - Dividend clienteles, The Dividend Decision - Information signalling, The Dividend Decision - Conclusion

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Decision making is the cognitive process of selecting a course of action from among multiple alternatives. Every decision-making produces a final choice. It can be an action or an opinion. It begins when we need to do something but we do not know what. Therefore decision-making is a reasoning process which can be rational or irrational, and can be based on explicit assumptions or tacit assumptions. Common examples include shopping, deciding what to eat, and deciding ...

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Decision making - Decision making style Decision making - Cognitive and personal biases in decision making Decision making - Cognitive neuroscience of decision making Decision making - Decision making in groups Decision making - Principles Decision making - Decision making in one's personal life Decision making - Decision making in healthcare Decision making - Path dependency Decision making - Decision making in business

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The complexity class P is the set of decision problems that can be solved by a deterministic machine in polynomial time. This class corresponds to an intuitive idea of the problems which can be effectively solved in the worst cases. The complexity class NP is the set of decision problems that can be solved by a non-deterministic machine in polynomial time. This class contains many problems that people would like to be able to solve effectively, including the Boolean satisfiability problem, the Hamiltonian path problem and the Vertex cover problem. All the problems in this cl ...

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Computational complexity theory, Computational complexity theory - Overview, Computational complexity theory - Decision problems, Computational complexity theory - Complexity classes, Computational complexity theory - The P = NP question, Computational complexity theory - Intractability, Computational complexity theory - Notable researchers

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In microeconomic theory, the partial equilibrium supply and demand economic model originally developed by Alfred Marshall attempts to describe, explain, and predict changes in the price and quantity of goods sold in competitive markets. The model is only a first approximation for describing an imperfectly competitive market. It formalizes the theories used by some economists before Marshall and is one of the most fundamental models of some modern economic schools, widely used as a basic building block in a wide range of more detailed ...

Including:

Supply and demand - Demand Supply and demand - Supply Supply and demand - Simple supply and demand curves
Supply and demand - Effects of being away from the equilibrium point
Supply and demand - Demand curve shifts Supply and demand - Supply curve shifts Supply and demand - Market clearance Supply and demand - Elasticity Supply and demand - Vertical supply curve Supply and demand - Other market forms Supply and demand - An example: Supply and demand in a 6-person economy Supply and demand - Decision making Supply and demand - History of supply and demand Supply and demand - Criticism of Marshall's theory of supply and demand Supply and demand - Special cases of a supply curve Supply and demand - External link and references

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A minimax algorithm is a recursive algorithm for choosing the next move in a two-player game. A value is associated with each position or state of the game. This value is computed by means of a position evaluation function and it indicates how good it would be for a player to reach that position. The player then makes the move that maximises the minimum value of the position resulting from the opponent's possible following moves. If it is A' ...

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Minimax, Minimax - Minimax criterion in statistical decision theory, Minimax - Minimax algorithm with alternate moves, Minimax - Minimax theorem with simultaneous moves, Minimax - Minimax in the face of uncertainty, Minimax - Minimax in non-zero-sum games, Minimax - External link

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Minimax theory has been extended to decisions where there is no other player, but where the consequences of decisions depend on unknown facts. For example, deciding to prospect for minerals entails a cost which will be wasted if the minerals are not present, but will bring major rewards if they are. One approach is to treat this as a game against Nature, and using a similar mindset as Murphy's law, take an approach which minimizes the maximum expected loss, using the same techniques as in the two-person zero-sum games. In addition, expectiminimax trees have been developed, for two ...

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Minimax, Minimax - Minimax criterion in statistical decision theory, Minimax - Minimax algorithm with alternate moves, Minimax - Minimax theorem with simultaneous moves, Minimax - Minimax in the face of uncertainty, Minimax - Minimax in non-zero-sum games, Minimax - External link

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The following example of a zero-sum game, where A and B make simultaneous moves, illustrates the minimax algorithm. If each player has three choices and the payoff matrix for A is: and B has the same payoff matrix with the signs reversed (i.e. if the choices are A1 and B1 then B pays 3 to A) then the simple minimax choice for A is A2 since the worst possible result is then having to pay 1, while the simple minimax choice for B is B2 since the worst possible result is then ...

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Minimax, Minimax - Minimax criterion in statistical decision theory, Minimax - Minimax algorithm with alternate moves, Minimax - Minimax theorem with simultaneous moves, Minimax - Minimax in the face of uncertainty, Minimax - Minimax in non-zero-sum games, Minimax - External link

Read more here: » Minimax: Encyclopedia II - Minimax - Minimax theorem with simultaneous moves

The question of whether P is the same set as NP is the most important open question in theoretical computer science. There is even a $1,000,000 prize for solving it. (See complexity classes P and NP and oracles). Questions like this motivate the concepts of hard and complete. A set of problems X is hard for a set of problems Y if every problem in Y can be transformed easily into some problem in X with the same answer. The definition of "easily" is different in different contexts. ...

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Computational complexity theory, Computational complexity theory - Overview, Computational complexity theory - Decision problems, Computational complexity theory - Complexity classes, Computational complexity theory - The P = NP question, Computational complexity theory - Intractability, Computational complexity theory - Notable researchers

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After the theory explaining which problems can be solved and which cannot be, it was natural to ask about the relative computational difficulty of computable functions. This is the subject matter of computational complexity. A single "problem" is an entire set of related questions, where each question is a finite-length string. For example, the problem FACTORIZE is: given an integer written in binary, return all of the prime factors of that number. A particular question is called an instance. For example, "give the factors of the ...

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Computational complexity theory, Computational complexity theory - Overview, Computational complexity theory - Decision problems, Computational complexity theory - Complexity classes, Computational complexity theory - The P = NP question, Computational complexity theory - Intractability, Computational complexity theory - Notable researchers

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Hofstadter[2] once suggested that people often find problems such as the PD problem easier to understand when it is illustrated in the form of a simple game, or trade-off. One of several examples he used was "closed bag exchange": Two people meet and exchange closed bags, with the understanding that one of them contains money, and the other contains a purchase. Either player can choose to honour the deal by putting into his bag wh ...

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Prisoner's dilemma, Prisoner's dilemma - The classical prisoner's dilemma, Prisoner's dilemma - Generalized form, Prisoner's dilemma - A similar but different game, Prisoner's dilemma - Real-life examples, Prisoner's dilemma - The iterated prisoner's dilemma, Prisoner's dilemma - Learning psychology and game theory, Prisoner's dilemma - Friend or Foe?, Prisoner's dilemma - Business decisions, Prisoner's dilemma - Notes

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In his book The Evolution of Cooperation (1984), Robert Axelrod explored an extension to the classical PD scenario, which he called the iterated prisoner's dilemma (IPD). In this, participants have to choose their mutual strategy again and again, and have memory of their previous encounters. Axelrod invited academic colleagues all over the world to devise computer strategies to compete in an IPD tournament. The programs that were entered varied widely in algorithmic ...

See also:

Prisoner's dilemma, Prisoner's dilemma - The classical prisoner's dilemma, Prisoner's dilemma - Generalized form, Prisoner's dilemma - A similar but different game, Prisoner's dilemma - Real-life examples, Prisoner's dilemma - The iterated prisoner's dilemma, Prisoner's dilemma - Learning psychology and game theory, Prisoner's dilemma - Friend or Foe?, Prisoner's dilemma - Business decisions, Prisoner's dilemma - Notes

Read more here: » Prisoner's dilemma: Encyclopedia II - Prisoner's dilemma - The iterated prisoner's dilemma

Hofstadter[2] once suggested that people often find problems such as the PD problem easier to understand when it is illustrated in the form of a simple game, or trade-off. One of several examples he used was "closed bag exchange": Two people meet and exchange closed bags, with the understanding that one of them contains money, and the other contains a purchase. Either player can choose to honour the deal by putting into his bag wh ...

See also:

Prisoner's dilemma, Prisoner's dilemma - The classical prisoner's dilemma, Prisoner's dilemma - Generalised form, Prisoner's dilemma - A similar but different game, Prisoner's dilemma - Real-life examples, Prisoner's dilemma - The iterated prisoner's dilemma, Prisoner's dilemma - Learning psychology and game theory, Prisoner's dilemma - Friend or Foe?, Prisoner's dilemma - Business decisions, Prisoner's dilemma - Notes

Read more here: » Prisoner's dilemma: Encyclopedia II - Prisoner's dilemma - A similar but different game

In his book The Evolution of Cooperation (1984), Robert Axelrod explored an extension to the classical PD scenario, which he called the iterated prisoner's dilemma (IPD). In this, participants have to choose their mutual strategy again and again, and have memory of their previous encounters. Axelrod invited academic colleagues all over the world to devise computer strategies to compete in an IPD tournament. The programs that were entered varied widely in algorithmic ...

See also:

Prisoner's dilemma, Prisoner's dilemma - The classical prisoner's dilemma, Prisoner's dilemma - Generalised form, Prisoner's dilemma - A similar but different game, Prisoner's dilemma - Real-life examples, Prisoner's dilemma - The iterated prisoner's dilemma, Prisoner's dilemma - Learning psychology and game theory, Prisoner's dilemma - Friend or Foe?, Prisoner's dilemma - Business decisions, Prisoner's dilemma - Notes

Read more here: » Prisoner's dilemma: Encyclopedia II - Prisoner's dilemma - The iterated prisoner's dilemma