---
layout: post-no-feature
title: "Deciding to Remember: Memory Maintenance as a Markov Decision Process"
description:
category: papers
type: Paper
journal: CogSci 2016
pdf: suchow2016mdp.pdf
tags: [memory maintenance, Markov Decision Process,
cognitive control, working memory]
---

Working memory is a limited-capacity form of human memory
that actively holds information in mind. Which memories
ought to be maintained? We approach this question by showing
an equivalence between active maintenance in working memory
and a Markov decision process in which, at each moment,
a cognitive control mechanism selects a memory as the target
of maintenance. The challenge of remembering is then finding
a maintenance policy well-suited to the task at hand. We compute
the optimal policy under various conditions and define
plausible cognitive mechanisms that can approximate these optimal
policies. Framing the problem of maintenance in this
way makes it possible to capture in a single model many of the
essential behavioral phenomena of memory maintenance, including
directed forgetting and self-directed remembering. Finally,
we consider the case of imperfect metamemory — where
the current state of memory is only partially observable — and
show that the fidelity of metamemory determines the effectiveness
of maintenance.

---
layout: post-no-feature
title: "Deciding to remember: memory maintenance as a Markov Decision Process"
description:
category: papers
type: Paper
journal: CogSci 2016
pdf: suchow2016mdp.pdf
tags: [memory maintenance, Markov Decision Process,
cognitive control, working memory]
---

Working memory is a limited-capacity form of human memory
that actively holds information in mind. Which memories
ought to be maintained? We approach this question by showing
an equivalence between active maintenance in working memory
and a Markov decision process in which, at each moment,
a cognitive control mechanism selects a memory as the target
of maintenance. The challenge of remembering is then finding
a maintenance policy well-suited to the task at hand. We compute
the optimal policy under various conditions and define
plausible cognitive mechanisms that can approximate these optimal
policies. Framing the problem of maintenance in this
way makes it possible to capture in a single model many of the
essential behavioral phenomena of memory maintenance, including
directed forgetting and self-directed remembering. Finally,
we consider the case of imperfect metamemory — where
the current state of memory is only partially observable — and
show that the fidelity of metamemory determines the effectiveness
of maintenance.

Improve title capitalization for consistency
Improve title capitalization for consistency
