Backwards induction in the centipede game

Analysis ◽  
1999 ◽  
Vol 59 (4) ◽  
pp. 237-242 ◽  
Author(s):  
J. Broome ◽  
W. Rabinowicz
Keyword(s):  
Backwards Induction

Virtual Implementation in Backwards Induction

1996 ◽  
Vol 15 (1) ◽  
pp. 27-32 ◽  
Author(s):  
Jacob Glazer ◽  
Motty Perry
Keyword(s):  
Backwards Induction

scholarly journals Every Choice Function Is Backwards-Induction Rationalizable

Econometrica ◽  
2013 ◽  
Vol 81 (6) ◽  
pp. 2521-2534 ◽  
Keyword(s):  
Choice Function ◽  
Backwards Induction

Consistent planning, backwards induction, and rule-governed behavior

1996 ◽  
Vol 7 (1) ◽  
pp. 35-48
Author(s):  
Christian Koboldt
Keyword(s):  
Backwards Induction ◽  
Rule Governed Behavior

Exact results for a secretary problem

1996 ◽  
Vol 33 (03) ◽  
pp. 630-639 ◽  
Author(s):  
M. P. Quine ◽  
J. S. Law
Keyword(s):  
Markov Chain ◽  
Optimal Strategy ◽  
Secretary Problem ◽  
Exact Results ◽  
Asymptotic Results ◽  
Backwards Induction ◽  
Imbedded Markov Chain ◽  
Probability Of Success

We consider the following secretary problem: items ranked from 1 to n are randomly selected without replacement, one at a time, and to ‘win' is to stop at an item whose overall rank is less than or equal to s, given only the relative ranks of the items drawn so far. Our method of analysis is based on the existence of an imbedded Markov chain and uses the technique of backwards induction. In principal the approach can be used to give exact results for any value of s; we do the working for s = 3. We give exact results for the optimal strategy, the probability of success and the distribution of T, and the total number of draws when the optimal strategy is implemented. We also give some asymptotic results for these quantities as n → ∞.

scholarly journals Backwards-induction outcome in a quantum game

2002 ◽  
Vol 65 (5) ◽  
Author(s):  
A. Iqbal ◽  
A. H. Toor
Keyword(s):  
Quantum Game ◽  
Backwards Induction

Cost rate heuristics for semi-Markov decision processes

1992 ◽  
Vol 29 (03) ◽  
pp. 633-644
Author(s):  
K. D. Glazebrook ◽  
Michael P. Bailey ◽  
Lyn R. Whitaker
Keyword(s):  
Dynamic Programming ◽  
Markov Decision Processes ◽  
Preventive Maintenance ◽  
Decision Processes ◽  
Cost Rate ◽  
Backwards Induction ◽  
Optimal Policies ◽  
Markov Decision ◽  
Speed Of Evolution

In response to the computational complexity of the dynamic programming/backwards induction approach to the development of optimal policies for semi-Markov decision processes, we propose a class of heuristics resulting from an inductive process which proceeds forwards in time. These heuristics always choose actions in such a way as to minimize some measure of the current cost rate. We describe a procedure for calculating such cost rate heuristics. The quality of the performance of such policies is related to the speed of evolution (in a cost sense) of the process. A simple model of preventive maintenance is described in detail. Cost rate heuristics for this problem are calculated and assessed computationally.

Energy storage systems in energy and ancillary markets: A backwards induction approach

2015 ◽  
Vol 147 ◽  
pp. 176-183 ◽  
Author(s):  
Joohyun Cho ◽  
Andrew N. Kleit
Keyword(s):  
Energy Storage ◽  
Storage Systems ◽  
Energy Storage Systems ◽  
Backwards Induction

The Logic of Backwards Inductions

2000 ◽  
Vol 16 (2) ◽  
pp. 267-285 ◽  
Author(s):  
Graham Priest
Keyword(s):  
Game Theory ◽  
Backwards Induction

Backwards induction is an intriguing form of argument. It is used in a number of different contexts. One of these is the surprise exam paradox. Another is game theory. But its use is problematic, at least sometimes. The purpose of this paper is to determine what, exactly, backwards induction is, and hence to evaluate it. Let us start by rehearsing informally some of its problematic applications.

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