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Sequential decision problems, dependent types and generic solutions
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dc.contributor.author | Botta, Nicola | |
dc.contributor.author | Jansson, Patrik | |
dc.contributor.author | Ionescu, Cezar | |
dc.contributor.author | Christiansen, David | |
dc.contributor.author | Brady, Edwin Charles | |
dc.date.accessioned | 2017-04-28T11:30:13Z | |
dc.date.available | 2017-04-28T11:30:13Z | |
dc.date.issued | 2017-03-17 | |
dc.identifier.citation | Botta , N , Jansson , P , Ionescu , C , Christiansen , D & Brady , E C 2017 , ' Sequential decision problems, dependent types and generic solutions ' , Logical Methods in Computer Science , vol. 13 , no. 1 , 7 . https://doi.org/10.23638/LMCS-13(1:7)2017 | en |
dc.identifier.issn | 1860-5974 | |
dc.identifier.other | PURE: 246979433 | |
dc.identifier.other | PURE UUID: ad0d5fc7-c663-4247-ae3e-1fb18b9608a4 | |
dc.identifier.other | Scopus: 85041811376 | |
dc.identifier.other | ORCID: /0000-0002-9734-367X/work/58054925 | |
dc.identifier.other | WOS: 000418916500015 | |
dc.identifier.uri | http://hdl.handle.net/10023/10681 | |
dc.description.abstract | We present a computer-checked generic implementation for solving finite horizon sequential decision problems. This is a wide class of problems, including intertemporal optimizations, knapsack, optimal bracketing, scheduling, etc. The implementation can handle time-step dependent control and state spaces, and monadic representations of uncertainty (such as stochastic, non-deterministic, fuzzy, or combinations thereof). This level of genericity is achievable in a programming language with dependent types (we have used both Idris and Agda). Dependent types are also the means that allow us to obtain a formalization and computer-checked proof of the central component of our implementation: Bellman’s principle of optimality and the associated backwards induction algorithm. The formalization clarifies certain aspects of backwards induction and, by making explicit notions such as viability and reachability, can serve as a starting point for a theory of controllability of monadic dynamical systems, commonly encountered in, e.g., climate impact research. | |
dc.format.extent | 23 | |
dc.language.iso | eng | |
dc.relation.ispartof | Logical Methods in Computer Science | en |
dc.rights | Copyright the Authors 2017. This work is licensed under the Creative Commons Attribution-NoDerivs License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nd/2.0/ | en |
dc.subject | BC Logic | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | T-NDAS | en |
dc.subject | BDC | en |
dc.subject | R2C | en |
dc.subject | SDG 13 - Climate Action | en |
dc.subject.lcc | BC | en |
dc.subject.lcc | QA75 | en |
dc.title | Sequential decision problems, dependent types and generic solutions | en |
dc.type | Journal article | en |
dc.description.version | Publisher PDF | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.identifier.doi | https://doi.org/10.23638/LMCS-13(1:7)2017 | |
dc.description.status | Peer reviewed | en |
dc.identifier.url | https://lmcs.episciences.org/3202 | en |
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