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Optimal instructional policies based on a random-trial incremental model of learning

Optimal instructional policies based on a random-trial incremental model of learning
Optimal instructional policies based on a random-trial incremental model of learning

The random-trial incremental (RTI) model of human associative learning proposes that learning due to a trial where the association is presented proceeds incrementally, but with a certain probability, constant across trials, no learning occurs due to a trial. Based on RTI, identifying a policy for sequencing presentation trials of different associations for maximizing overall learning can be accomplished via a factored Markov decision process (MDP). For both finite and infinite horizons and a quite general structure of costs and rewards, a policy that on each trial presents an association that leads to the maximum expected immediate net reward is optimal.

1083-4427
490-494
Katsikopoulos, K. V.
b97c23d9-8b24-4225-8da4-be7ac2a14fba
Katsikopoulos, K. V.
b97c23d9-8b24-4225-8da4-be7ac2a14fba

Katsikopoulos, K. V. (2000) Optimal instructional policies based on a random-trial incremental model of learning. IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans., 30 (4), 490-494. (doi:10.1109/3468.852441).

Record type: Article

Abstract

The random-trial incremental (RTI) model of human associative learning proposes that learning due to a trial where the association is presented proceeds incrementally, but with a certain probability, constant across trials, no learning occurs due to a trial. Based on RTI, identifying a policy for sequencing presentation trials of different associations for maximizing overall learning can be accomplished via a factored Markov decision process (MDP). For both finite and infinite horizons and a quite general structure of costs and rewards, a policy that on each trial presents an association that leads to the maximum expected immediate net reward is optimal.

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More information

Published date: 1 July 2000

Identifiers

Local EPrints ID: 439256
URI: http://eprints.soton.ac.uk/id/eprint/439256
ISSN: 1083-4427
PURE UUID: f2fb0ee6-f248-4dc9-ae88-b1e29db2e4ff
ORCID for K. V. Katsikopoulos: ORCID iD orcid.org/0000-0002-9572-1980

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Date deposited: 07 Apr 2020 16:31
Last modified: 09 Jan 2022 03:55

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