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4 changes: 2 additions & 2 deletions DESCRIPTION
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Package: catlearn
Type: Package
Title: Formal Psychological Models of Categorization and Learning
Version: 0.9.3
Date: 2022-10-06
Version: 1.0
Date: 2023-04-04
Encoding: UTF-8
Author: Andy Wills, Lenard Dome, Charlotte Edmunds, Garrett Honke, Angus Inkster, René Schlegelmilch, Stuart Spicer
Maintainer: Andy Wills <andy@willslab.co.uk>
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16 changes: 10 additions & 6 deletions docs/CHANGELOG.md
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Expand Up @@ -4,19 +4,23 @@ All notable changes to this project will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/)

## Version 1.0 [unreleased]
## Version 1.0 [cran]

## Added
### Added

- **slpDGCM** [model] introduce the implementation of similarity-dissimilarity general-context model (Stewart and Morin, 2007), that also includes settings to run the version of O'Bryan et al. (2018). ([@lenarddome](https://github.com/lenarddome))

### Changed

- **slpDGCM** [model] introduce the implemention of similarity-dissimilarity general-context model (Stewart and Morin, 2007), that also includes settings to run the version of O'Bryan et al. (2018). ([@lenarddome](https://github.com/lenarddome))
- **slpSUSTAIN** [model] Enhancement: add probability of item being reported as 'old'.

## Version 0.9.1 [cran]
## Version 0.9.1

## Added
### Added

- **slpNNCAG, slpNNRAS** [model] Added Models 4 and 5 from Paskewitz & Jones (2020). ([@lenarddome](https://github.com/lenarddome))

## Changed
### Changed

- **slpEXIT** [code] [4af799d23adb8f8d42e2479adcb64855709e24bc](https://github.com/ajwills72/catlearn/commit/4af799d23adb8f8d42e2479adcb64855709e24bc) Minor tweak to fix linux+clang14 warning ([@ajwills72](https://www.andywills.info))

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172 changes: 60 additions & 112 deletions docs/README.md
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Expand Up @@ -31,32 +31,34 @@ The latest stable version of catlearn contains the following:
- ALCOVE (_slpALCOVE_), see also our [description of ALCOVE](desc-alcove.pdf)

- COVIS (_slpCOVIS_)


- DGCM (_slpDGCM_)

- DIVA (_slpDIVA_)

- EXIT and two 'dissected' versions thereof (_slpEXIT_, _slpNNCAG_ and _slpNNRAS_)

- GCM (_stsimGCM_)

- SUSTAIN (_slpSUSTAIN_)

### Contingency learning

- Bush-Mosteller (_slpBM_)

- Gluck & Bower (1988) (_slpLMSnet_)

- MBMF: model-based, model-free hybrid (_slpMBMF_)

- Mackintosh (1975) (_slpMack75_)

- Rescorla-Wagner (_slpRW_)

## Simulations

Simulations of several dataset-model combinations (e.g. krus96exit is a simulation of the krus96 dataset with the slpEXIT model). In some cases:

- the optimization routines are available (functions ending _opt_).
- the optimization routines are available (functions ending _opt_).

- functions to generate input representations for the models are separately available, to facilitate re-use (functions ending _train_).

Expand All @@ -67,53 +69,53 @@ Simulations of several dataset-model combinations (e.g. krus96exit is a simulati
### Inverse base-rate effect (_krus96_)

- krus96exit

- krus96train

### Stimulus frequency effect (_nosof88_)

- nosof88exalcove

- nosof88exalcove_opt

- nosof88oat

- nosof88protoalcove

- nosof88protoalcove_opt

- nosof88train

### Type I-VI problems (_nosof94_)

- nosof94bnalcove

- nosof94exalcove

- nosof94exalcove_opt

- nosof94oat

- nosof95plot

- nosof94sustain

- nosof94train

### Category size (_shin92_)

- shin92exalcove

- shin92exalcove_opt

- shin92oat

- shin92protoalcove

- shin92protoalcove_opt

- shin92train

## Support functions

- act2probrat (convert output model activation to a predicted rating).
Expand All @@ -126,7 +128,7 @@ Simulations of several dataset-model combinations (e.g. krus96exit is a simulati

If you'd like to contribute to this project by adding models,
datasets, or simulations to the catlearn package,
contact Andy Wills.
contact Andy Wills.

# Invite us to give a talk or workshop

Expand All @@ -140,139 +142,85 @@ accommodation.
The Catlearn Research Group are based in the United Kingdom,
[Plymouth University](http://www.openstreetmap.org/way/42361939)

Previous talks and workshops have included:

### 2020

**The OpenModels project**
_Andy Wills_. 8th September 2020.
UK network of Open Research Working Groups (virtual meeting), MRC-CBU, Cambridge, UK
Talk available on [youtube](https://www.youtube.com/watch?v=SfqkqEYagJU&list=PLOA0aRJ90NxvXtMt5Si5ukmR9LYfvDueB&index=10&t=0s).

### 2019

**Benchmark phenomena in category learning**.
_Andy Wills_. 22nd June 2019.
Annual Summer Interdisciplinary Conference (ASIC), Seefeld, Austria.

**The OpenModels project in category learning**.
_Stuart Spicer and Angus Inkster_. 14th June 2019.
Open Science symposium. Plymouth University, UK.

**Progress in modelling through distributed collaboration**.
_Andy Wills_. 16th April 2019.
Tagung Experimentell Arbeitender Psychologen (TEAP) conference, London, UK

**Progress in modelling through distributed collaboration**.
_Andy Wills_. 21st March 2019.
Open Science symposium. University of Ghent, Belgium.

**Progress in modelling through distributed collaboration**.
_Andy Wills_. 7th March 2019.
PRomoting Open Science PRactices (PROSPR) seminar series, Lancaster University, UK

### 2018

**Progress in modelling through distributed collaboration**.
_Andy Wills_. 19th June 2018.
International Category Learning Symposium, Plymouth, UK.

**An introduction to the Open Models project**.
_Andy Wills_. 28th March 2018.
Associative Learning Symposium, Gregynog, Wales.

### 2017

**An introduction to the Open Models project**.
_Andy Wills_. 27th October 2017.
School of Psychology, Cardiff University, UK.

**A Practical Introduction to Distributed Collaboration for Formal Modeling**.
_Andy Wills and Charlotte Edmunds_, 22nd July 2017. 50th Annual Meeting of the Society for Mathematical Psychology, University of Warwick, UK.

**Progress in learning theory through distributed collaboration**. _Andy Wills_, 11th April 2017. Associative Learning Symposium, Gregynog, Wales.

**A Practical Introduction to Distributed Collaboration for Formal Modeling**.
_Andy Wills_, 23rd March 2017. International Convention of Psychological Science, Vienna, Austria.

**Progress in modelling through distributed collaboration**. _Andy Wills_, Jan 2017. Experimental Psychology Society, London, UK.

**Introduction to catlearn**. _Andy Wills_. 26th Jan 2017. School of Psychology, Plymouth University, UK.

# Roadmap

We aim to release version 1.0 to CRAN by 28st March 2023.
We aim to release version 1.1 to CRAN by 26th March 2024.

Contributions of working, tested, Rd-documented code are welcome for consideration at any time. Where code is ready for inclusion into catlearn, it will first be released to the community as an unstable point release of catlearn on github. On 14th March 2023, the latest unstable release on github will be used to check and build stable version 1.0 for release to CRAN.
Contributions of working, tested, Rd-documented code are welcome for consideration at any time. Where code is ready for inclusion into catlearn, it will first be released to the community as an unstable point release of catlearn on github. On 12th March 2024, the latest unstable release on github will be used to check and build stable version 1.1 for release to CRAN.

# History

Dates of CRAN releases, along with email-list announcements (from 0.7.2, see
[CHANGELOG](CHANGELOG.md) for more detail of changes):

- Version 1.0.x ("Juicy Jam") _future_
- Version 1.1.x. ("Krispy Kreme") _future_

- Version 1.0.x ("Juicy Jam") _CURRENT_

- 2023-04-04: Version 1.0. **stable release** on its way to CRAN. [announcement](announce/version-1.0-email.txt).

- Version 0.9.x ("Incredible Icing") _CURRENT_
- Version 0.9.x ("Incredible Icing")

- 2022-10-06: Version 0.9.3. **unstable release** on github: Add slpDGCM - implementation of the similarity-dissimilarity generalized context model of Stewart & Morin (2007), and the variant used by O'Bryan et al. (2018).
- 2022-10-06: Version 0.9.3. Add slpDGCM - implementation of the similarity-dissimilarity generalized context model of Stewart & Morin (2007), and the variant used by O'Bryan et al. (2018).

- 2022-09-22: Version 0.9.2. Enhancement to slpSUSTAIN: add probability of item being reported as 'old'.
- 2022-09-22: Version 0.9.2. Enhancement to slpSUSTAIN: add probability of item being reported as 'old'.

- 2022-03-28: Version 0.9.1. **stable release** on CRAN. [announcement](announce/version-0.9-email.txt).
- 2022-03-28: Version 0.9.1. stable release on CRAN. [announcement](announce/version-0.9-email.txt).

- 2022-03-25: Version 0.9 - Release to CRAN subsequently discovered to generate a warning when compiled with clang 14 on linux.
- 2022-03-25: Version 0.9 - Release to CRAN subsequently discovered to generate a warning when compiled with clang 14 on linux.

- Version 0.8.x ("Harmonious honey")
- Version 0.8.x ("Harmonious honey")

- 2022-01-18: Version 0.8.3: edge-case installation bug fix (see changelog)
- 2022-01-18: Version 0.8.3: edge-case installation bug fix (see changelog)

- 2022-01-10: Version 0.8.2: slpLMSnet documentation improvements, plus addition of ratio-rule response function as an option.
- 2022-01-10: Version 0.8.2: slpLMSnet documentation improvements, plus addition of ratio-rule response function as an option.

- 2022-01-05: Version 0.8.1: slpNNCAG and slpNNRAS added, implements Models 4 and 5 from Paskewitz & Jones (2020).
- 2022-01-05: Version 0.8.1: slpNNCAG and slpNNRAS added, implements Models 4 and 5 from Paskewitz & Jones (2020).

- 2020-09-16: Version 0.8: stable release on CRAN. [announcement](announce/version-0.8-email.txt).
- 2020-09-16: Version 0.8: stable release on CRAN. [announcement](announce/version-0.8-email.txt).

- Version 0.7.x ("Gooey chocolate")
- Version 0.7.x ("Gooey chocolate")

- 2020-08-06: Version 0.7.5: slpLMSnet added, implements Gluck & Bower (1988).
- 2020-08-06: Version 0.7.5: slpLMSnet added, implements Gluck & Bower (1988).

- 2020-07-01: Version 0.7.4: fix for slpSUSTAIN bug introduced in 0.7.2.
- 2020-07-01: Version 0.7.4: fix for slpSUSTAIN bug introduced in 0.7.2.

- 2020-05-15: Version 0.7.3: slpALCOVE upgraded to include some checks for user errors in model specification.
- 2020-05-15: Version 0.7.3: slpALCOVE upgraded to include some checks for user errors in model specification.

- 2020-05-13: Version 0.7.2: slpSUSTAIN upgraded to: (a) improve implementation of cluster recruitment in edge cases not covered in Love et al. (2004), and (b) add basic checking of common user errors.
- 2020-05-13: Version 0.7.2: slpSUSTAIN upgraded to: (a) improve implementation of cluster recruitment in edge cases not covered in Love et al. (2004), and (b) add basic checking of common user errors.

- 2019-10-10: Version 0.7.1: Stable release on CRAN. [announcement](announce/version-0.7.1-email.txt).
- 2019-10-10: Version 0.7.1: Stable release on CRAN. [announcement](announce/version-0.7.1-email.txt).

- Version 0.6.x ("Fried chicken")

- 2019-10-03: Version 0.6.5: slpSUSTAIN uprgaded to include unsupervised category learning.
- 2019-10-03: Version 0.6.5: slpSUSTAIN uprgaded to include unsupervised category learning.

- 2019-10-02: Version 0.6.4: slpMack75 added.

- 2019-05-23: Version 0.6.3: slpEXIT converted to C++ for speed.

- 2019-10-02: Version 0.6.4: slpMack75 added.

- 2019-05-23: Version 0.6.3: slpEXIT converted to C++ for speed.
- 2019-03-18: Version 0.6.2: Minor patch so packages tests work on R 3.6.0.

- 2019-03-18: Version 0.6.2: Minor patch so packages tests work on R 3.6.0.
- 2019-02-18: Version 0.6.1: Stable release on CRAN. Minor maintenance release. [announcement](announce/version-0.6.1-email.txt).

- 2019-02-18: Version 0.6.1: Stable release on CRAN. Minor maintenance release. [announcement](announce/version-0.6.1-email.txt).
- 2018-07-17: Version 0.6: Stable release on CRAN. slpEXIT and slpSUSTAIN added. [announcement](announce/version-0.6-email.txt).

- 2018-07-17: Version 0.6: Stable release on CRAN. slpEXIT and slpSUSTAIN added. [announcement](announce/version-0.6-email.txt).
- Version 0.5 ("Excellent bacon")

- Version 0.5 ("Excellent bacon")
- 2017-12-11: Stable release on CRAN [announcement](announce/version-0.5-email.txt).

- 2017-12-11: Stable release on CRAN [announcement](announce/version-0.5-email.txt).

- Version 0.4 ("Dinky doughnut")

- 2017-02-23: Stable release on CRAN [announcement](announce/version-0.4-email.txt).
- 2017-02-23: Stable release on CRAN [announcement](announce/version-0.4-email.txt).

- Version 0.3 ("Cream cake")
- Version 0.3 ("Cream cake")

- 2016-08-18: Stable release on CRAN [announcement](announce/version-0.3-email.txt).
- 2016-08-18: Stable release on CRAN [announcement](announce/version-0.3-email.txt).

- Versions 0.1, 0.2 (not named)

- These were internal development versions, never publicly released.
- These were internal development versions, never publicly released.

# References

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Hi,

Version 1.0 of the 'catlearn' package is now available.

Catlearn is an archive of fourteen formal models of categorization and
learning. It's free and open source software ... and always will be. It has
been downloaded 37,000 times.

Version 1.0 is an upgrade release with one new model (DGCM, in both the original
Stewart & Morin, 2007, form and the more recent O'Bryan et al., 2018, form),
and one model upgrade (SUSTAIN, which now reports the probability that a
presented stimulus is 'old').

Catlearn is a package for R, and is very easy to install within that
environment. Make sure you're running the latest version of R, and then type:

install.packages('catlearn')

and then

library(catlearn).

For a tutorial introduction to catlearn, see Wills et al. (2017). There is also
information here:

https://andywills.info/catlearn

Thanks to all the contributors to catlearn, and particular thanks to Lenard
Dome who contributed new code for the version 1.0 release.

All the best

Andy
2023-04-05

Wills, A.J., O'Connell, G., Edmunds, C.E.R., & Inkster, A.B.(2017). Progress in
modeling through distributed collaboration: Concepts, tools, and
category-learning examples. The Psychology of Learning and Motivation

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