The Revenge of Ecological Rationality: Strategy-Selection by Meta-Induction Within Changing Environments
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According to the paradigm of adaptive rationality, successful inference and prediction methods tend to be local and frugal. As a complement to work within this paradigm, we investigate the problem of selecting an optimal combination of prediction methods from a given toolbox of such local methods, in the context of changing environments. These selection methods are called meta-inductive (MI) strategies, if they are based on the success-records of the toolbox-methods. No absolutely optimal MI strategy exists—a fact that we call the “revenge of ecological rationality”. Nevertheless one can show that a certain MI strategy exists, called “AW”, which is universally long-run optimal, with provably small short-run losses, in comparison to any set of prediction methods that it can use as input. We call this property universal access-optimality. Local and short-run improvements over AW are possible, but only at the cost of forfeiting universal access-optimality. The last part of the paper includes an empirical study of MI strategies in application to an 8-year-long data set from the Monash University Footy Tipping Competition.
KeywordsPrediction task Adaptive rationality Strategy selection Meta-induction Online learning
Work on this paper was supported by the DFG Grant SCHU1566/9-1 as part of the priority program “New Frameworks of Rationality” (SPP 1516). For valuable help we are indebted to K.V. Katsikopolous, Ö. Simsek, A.P. Pedersen, R. Hertwig, M. Jekel, P. Grunwald, J.-W. Romeijn, and L. Martignon.
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