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On the correctness of monadic backward induction

Published online by Cambridge University Press:  29 October 2021

NURIA BREDE Open the ORCID record for NURIA BREDE [Opens in a new window]  and
NICOLA BOTTA Open the ORCID record for NICOLA BOTTA [Opens in a new window]
NURIA BREDE
Affiliation:
University of Potsdam, Potsdam, Germany Potsdam Institute for Climate Impact Research, Potsdam, Germany (e-mail: [email protected])
NICOLA BOTTA
Affiliation:
Potsdam Institute for Climate Impact Research, Potsdam, Germany Chalmers University of Technology, Göteborg, Sweden (e-mail: [email protected])
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Abstract

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In control theory, to solve a finite-horizon sequential decision problem (SDP) commonly means to find a list of decision rules that result in an optimal expected total reward (or cost) when taking a given number of decision steps. SDPs are routinely solved using Bellman’s backward induction. Textbook authors (e.g. Bertsekas or Puterman) typically give more or less formal proofs to show that the backward induction algorithm is correct as solution method for deterministic and stochastic SDPs. Botta, Jansson and Ionescu propose a generic framework for finite horizon, monadic SDPs together with a monadic version of backward induction for solving such SDPs. In monadic SDPs, the monad captures a generic notion of uncertainty, while a generic measure function aggregates rewards. In the present paper, we define a notion of correctness for monadic SDPs and identify three conditions that allow us to prove a correctness result for monadic backward induction that is comparable to textbook correctness proofs for ordinary backward induction. The conditions that we impose are fairly general and can be cast in category-theoretical terms using the notion of Eilenberg–Moore algebra. They hold in familiar settings like those of deterministic or stochastic SDPs, but we also give examples in which they fail. Our results show that backward induction can safely be employed for a broader class of SDPs than usually treated in textbooks. However, they also rule out certain instances that were considered admissible in the context of Botta et al. ’s generic framework. Our development is formalised in Idris as an extension of the Botta et al. framework and the sources are available as supplementary material.

Type
Research Article
Information
Journal of Functional Programming , Volume 31 , 2021 , e26
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Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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