Economic subjects | Decision theory » Claudia Passagallo - Causal Decision Theory

Source: http://www.doksinet CAUSAL DECISION THEORY Claudia Passagallo - matricola n. 73353 Causal decision theory is the view that a rational decision maker should keep all her beliefs about causal processes fixed in the decision-making process,and always choose an alternative that is optimal according to these beliefs. So, causal decision theory adopts principles of rational choice that attend to an act’s consequences. It maintains that an account of rational choice must use causality to identify the considerations that make a choice rational. Given a set of options constituting a decision problem, decision theory recommends an option that maximizes utility, that is, an option whose utility equals or exceeds the utility of every other option. It evaluates an option’s utility by calculating the option’s expected utility It uses probabilities and utilities of an option’s possible outcomes to define an option’s expected utility. The probabilities depend on the option.

Example. A possible example can be: if eating an humburger will make you happy while eating a salad will make you sad then you would be rational to eat the humburger. One complication is the notion of expected causal consequences. Now, the problem is that if eating a good humburger will make you happy and eating a bad humburger will make you sad but you are not sure if the humburger is good or bad. In this case you dont know the causal effects of eating the humburger. Instead, then, you work from the expected causal effects, where these will depend on three things: 1) how likely you think the humburger is to be good and how likely you think it is to be bad; 2) how happy eating a good humburger makes you; 3) how sad eating a bad humburger makes you. So, causal decision theory advises the agent to make the decision with the best expected causal effects. In a 1981 article, Allan Gibbard and William Harper explained causal decision theory as maximization of the expected utility U of an

action A of an action "calculated from probabilities of counterfactuals": U(A) =∑� �(� > ��)�(��), where D (Oj) is the desirability of outcome Oj and P(A>Oj) is the counterfactual probability that, if A were done, then Oj would hold. THEORY IN OPPOSITION: EVIDENTIAL DECISION THEORY The causal decision theory is in opposition with evidential decision theory, which recommends those actions that provide the best evidence about the world. So, we take the action that gives the best news about the outcome. Source: http://www.doksinet CRITICISM: NEWCOMB’S PARADOX Newcombs paradox is a classic example illustrating the potential conflict between causal and evidential decision theory. Newcombs paradox was created by William Newcomb of the University of Californias Lawrence Livermore Laboratory. According to this paradox we have 2 boxes (box A and box B) and a Predictor says that in the box A there are € 1.000 and in the box B there are € 0 or €

1000000 At this point we should choose both boxes or only box B. The predictor says that if you choose the box B there will be 1.000000 euro (but you are not sure at 100%) while if you choose both the boxes then in the box B there will be 0 euro (but you are not sure at 100%). This paradox arises baecause there are 2 strategies with 2 opposite behaviors: 1) In the first case you follow the principle of utility, the option that maximizes utility choosing the box B; 2) In the second case you follow the principle of dominance choosing both the boxes. The reasoning is contradictory, to solve the paradox or you consider one of the two irrational principles or that all is impossible. So, Newcomb’s paradox shows that the utility and dominance principles are correct and that the foresight is impossible. REFERENCES  M. Peterson, An introduction to decision theory, Cambridge University (2009)  www.platostanfordedu  www.enwikipediaorg  www.wikilesswrongcom 

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