Elliptic function

2013-12-03T04:13:24Z

69.115.47.90: /* Weierstrass's elliptic functions */

{{more footnotes|date=November 2009}}

'''Bounded rationality''' is the idea that in decision-making, rationality of individuals is limited by the information they have, the cognitive limitations of their minds, and the finite amount of time they have to make a decision. It was proposed by [[Herbert A. Simon]] as an alternative basis for the mathematical modeling of decision making, as used in [[economics]] and related disciplines; it complements ''rationality as optimization'', which views decision-making as a fully rational process of finding an optimal choice given the information available.<ref name=bounded_rationality_1999>{{cite book|url=http://books.google.com/?id=dVMq5UoYS3YC&dq=%22bounded+rationality%22&printsec=frontcover|first=Gerd|last=Gigerenzer|first2=Reinhard|last2=Selten|title=Bounded Rationality: The Adaptive Toolbox|publisher=MIT Press|year=2002|isbn=0-262-57164-1}}</ref> Another way to look at bounded rationality is that, because decision-makers lack the ability and resources to arrive at the optimal solution, they instead apply their rationality only after having greatly simplified the choices available. Thus the decision-maker is a [[satisficer]], one seeking a satisfactory solution rather than the optimal one.<ref>{{cite web|url=http://www.answers.com/topic/bounded-rationality|title=Bounded rationality: Definition from Answers.com|publisher=Answers Corporation|accessdate=2009-04-12}}</ref> Simon used the analogy of a pair of scissors, where one blade is the "cognitive limitations" of actual humans and the other the "structures of the environment"; minds with limited cognitive resources can thus be successful by exploiting pre-existing structure and regularity in the environment.<ref name=bounded_rationality_1999/>

Some models of [[human behavior]] in the [[social sciences]] assume that [[humans]] can be reasonably approximated or described as "[[rationality|rational]]" entities (see for example [[rational choice theory]]). Many [[economics]] models assume that people are on average rational, and can in large enough quantities be approximated to act according to their [[preference]]s. The concept of bounded rationality revises this assumption to account for the fact that perfectly rational decisions are often not feasible in practice because of the finite computational resources available for making them.

==Origins==
The term is thought to have been coined by [[Herbert A. Simon]]. In ''Models of Man'', Simon points out that most people are only partly rational, and are irrational in the remaining part of their actions. In another work, he states "boundedly rational agents experience limits in formulating and solving complex problems and in processing (receiving, storing, retrieving, transmitting) [[information]]".<ref>[[Oliver E. Williamson]], p. 553, citing Simon.</ref> Simon describes a number of dimensions along which "classical" models of rationality can be made somewhat more realistic, while sticking within the vein of fairly rigorous formalization. These include:

* Limiting the types of [[utility]] functions
* Recognizing the costs of gathering and processing information
* Possibility of having a "[[vector (geometry)|vector]]" or "multi-valued" utility function

Simon suggests that economic agents use [[heuristics in judgment and decision making|heuristics]] to make decisions rather than a strict rigid rule of optimization. They do this because of the complexity of the situation, and their inability to process and compute the expected utility of every alternative action. Deliberation costs might be high and there are often other concurrent economic activities also requiring decisions.

==Model Extensions==

As decision makers have to make decisions about how and when to decide, [[Ariel Rubinstein]] proposed to [http://arielrubinstein.tau.ac.il/book-br.html model-bounded rationality] by explicitly specifying decision-making procedures. This puts the study of decision procedures on the research agenda.

[[Gerd Gigerenzer]] opines that decision theorists have not really adhered to Simon's original ideas. Rather, they have considered how decisions may be crippled by limitations to rationality, or have modeled how people might cope with their inability to optimize. Gigerenzer proposes and shows that simple [[heuristic]]s often lead to better decisions than theoretically optimal procedures.

[[Huw Dixon]] later argues that it may not be necessary to analyze in detail the process of reasoning underlying bounded rationality.<ref>{{cite book |chapter=Some Thoughts on Artificial Intelligence and Economic Theory |editor-last=Moss |editor2-last=Rae |title=Artificial Intelligence and Economic Analysis |publisher=Edward Elgar |location= |year=1992 |pages=131–154 |doi= |isbn=185278685X }}</ref> If we believe that agents will choose an action that gets them "close" to the optimum, then we can use the notion of '''epsilon-optimization''', that means you choose your actions so that the payoff is within epsilon of the optimum. If we define the optimum (best possible) payoff as <math> U^* </math>, then the set of epsilon-optimizing options '''S(ε)''' can be defined as all those options '''s''' such that:

<math> U(s) \geq U^*-\epsilon</math>.

The notion of strict rationality is then a special case (ε=0). The advantage of this approach is that it avoids having to specify in detail the process of reasoning, but rather simply assumes that whatever the process is, it is good enough to get near to the optimum.

From a computational point of view, decision procedures can be encoded in [[algorithms]] and [[heuristics]]. [[Edward Tsang]] argues that the effective rationality of an agent is determined by its [[computational intelligence]]. Everything else being equal, an agent that has better algorithms and heuristics could make "more rational" (more optimal) decisions than one that has poorer heuristics and algorithms.

==See also==
{{div col|colwidth=30em}}
*''[[Administrative Behavior]]''
*[[Altruism]]
*[[Analysis paralysis]]
*[[Behavioral economics]]
*[[Carnegie School]]
*[[Concept driven strategy]]
*[[Cognitive bias]]
*[[Heuristics]]
*[[Homo economicus]]
*[[Neoclassical economics]]
*[[Organizing principle]]
*[[Parametric determinism]]
*[[Prospect theory]]
*[[Psychohistory]]
*[[Rational ignorance]]
*[[Satisficing]]
*[[Social heuristics]]
*[[Subjective theory of value]]
*[[Transaction cost]]
*[[Utility maximization problem]]
{{Div col end}}

==Notes==
{{reflist}}

==References==
{{Refbegin|60em}}
*{{cite book |author=Elster, Jon |title=Sour Grapes: Studies in the Subversion of Rationality |publisher=Cambridge University Press |location=Cambridge, UK |year=1983 |isbn=0-521-25230-X }}
*{{cite book |author=Gigerenzer, Gerd and Selten, Reinhard |title=Bounded Rationality |publisher=MIT Press |location=Cambridge |year=2002 |isbn=0-262-57164-1 }}
* Hayek, F.A (1948) Individualism and Economic order
*{{cite journal |doi=10.1257/000282803322655392 |author=Kahneman, Daniel |title=Maps of bounded rationality: psychology for behavioral economics |journal=The American Economic Review |volume=93 |issue=5 |pages=1449–75 |year=2003 }}
*{{cite book |author=March, James G. |title=A Primer on Decision Making: How Decisions Happen |publisher=The Free Press |location=New York |year=1994 |isbn=0-02-920035-0 }}
*{{cite book |author=Rubinstein, Ariel |title=Modeling bounded rationality |publisher=MIT Press |year=1998 |isbn=0-585-05347-2 }}
* Simon, Herbert (1957). "A Behavioral Model of Rational Choice", in Models of Man, Social and Rational: Mathematical Essays on Rational Human Behavior in a Social Setting. New York: Wiley.
*{{cite book |author=March, James G. and Simon, Herbert | title=Organizations |publisher=John Wiley and Sons |year=1958 |isbn=0-471-56793-0 }}
*{{cite journal |doi=10.1126/science.2270480 |author=Simon, Herbert |title=A mechanism for social selection and successful altruism |journal=Science |volume=250 |issue=4988 |pages=1665–8 |year=1990 |pmid=2270480 }}
*{{cite journal |doi=10.1287/orsc.2.1.125 |author=Simon, Herbert |title=Bounded Rationality and Organizational Learning |journal=Organization Science |volume=2 |issue=1 |pages=125–134 |year=1991 }}
*{{cite book |author=Tisdell, Clem |title=Bounded Rationality and Economic Evolution: A Contribution to Decision Making, Economics, and Management |publisher=Brookfield |location=Cheltenham, UK |year=1996 |isbn=1-85898-352-5 }}
*{{cite journal |doi=10.1007/s11633-008-0063-6 |author=Tsang, E.P.K. |title=Computational intelligence determines effective rationality |journal=International Journal on Automation and Control |volume=5 |issue=1 |pages=63–6 |year=2008 }}
*{{cite journal |author=Williamson, Oliver E.|title=The economics of organization: the transaction cost approach |journal=American Journal of Sociology |volume=87 |issue=3 |pages=[http://www.polisci.ucsd.edu/gcox/06%20Ollie.pdf 548–577] (press '''+''').|year=1981 }}
{{Refend}}

==External links==
* [http://choo.fis.utoronto.ca/FIS/courses/lis2149/kahneman.NobelPrize.pdf Mapping Bounded Rationality by Daniel Kahneman]
* [http://www.huwdixon.org/SurfingEconomics/chapter7.pdf Artificial Intelligence and Economic Theory] chapter 7 of [http://huwdixon.org/SurfingEconomics/index.html Surfing Economics] by [[Huw Dixon]].

{{game theory}}

[[Category:Behavioral economics]]
[[Category:Game theory]]
[[Category:Underlying principles of microeconomic behavior]]

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