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1
Optimal decision making and matching are tied through diminishing returns.
Proc Natl Acad Sci U S A. 2017 Aug 8;114(32):8499-8504. doi: 10.1073/pnas.1703440114. Epub 2017 Jul 24.
2
When does reward maximization lead to matching law?
PLoS One. 2008;3(11):e3795. doi: 10.1371/journal.pone.0003795. Epub 2008 Nov 24.
3
Operant matching as a Nash equilibrium of an intertemporal game.
Neural Comput. 2009 Oct;21(10):2755-73. doi: 10.1162/neco.2009.09-08-854.
4
Worth the Work? Monkeys Discount Rewards by a Subjective Adapting Effort Cost.
J Neurosci. 2023 Oct 4;43(40):6796-6806. doi: 10.1523/JNEUROSCI.0115-23.2023. Epub 2023 Aug 25.
5
Matching Behavior as a Tradeoff Between Reward Maximization and Demands on Neural Computation.
F1000Res. 2015 Jun 9;4:147. doi: 10.12688/f1000research.6574.2. eCollection 2015.
6
The actor-critic learning is behind the matching law: matching versus optimal behaviors.
Neural Comput. 2008 Jan;20(1):227-51. doi: 10.1162/neco.2008.20.1.227.
7
Statistical mechanics of reward-modulated learning in decision-making networks.
Neural Comput. 2012 May;24(5):1230-70. doi: 10.1162/NECO_a_00264. Epub 2012 Feb 1.
8
Neuroeconomics: the consilience of brain and decision.
Science. 2004 Oct 15;306(5695):447-52. doi: 10.1126/science.1102566.
9
The role of moral utility in decision making: an interdisciplinary framework.
Cogn Affect Behav Neurosci. 2008 Dec;8(4):390-401. doi: 10.3758/CABN.8.4.390.
10
Matching provides efficient decisions.
Res Sq. 2024 Feb 14:rs.3.rs-3949086. doi: 10.21203/rs.3.rs-3949086/v1.

引用本文的文献

2
Matching provides efficient decisions.
bioRxiv. 2024 Feb 19:2024.02.15.580481. doi: 10.1101/2024.02.15.580481.
3
Developmental feedbacks and the emergence of individuality.
R Soc Open Sci. 2022 Nov 30;9(11):221189. doi: 10.1098/rsos.221189. eCollection 2022 Nov.
4
Reward foraging task and model-based analysis reveal how fruit flies learn value of available options.
PLoS One. 2020 Oct 2;15(10):e0239616. doi: 10.1371/journal.pone.0239616. eCollection 2020.
5
Optimal response vigor and choice under non-stationary outcome values.
Psychon Bull Rev. 2019 Feb;26(1):182-204. doi: 10.3758/s13423-018-1500-3.

本文引用的文献

1
Matching Behavior as a Tradeoff Between Reward Maximization and Demands on Neural Computation.
F1000Res. 2015 Jun 9;4:147. doi: 10.12688/f1000research.6574.2. eCollection 2015.
2
On the theoretical and empirical status of the matching law and matching theory.
Psychol Bull. 2013 Sep;139(5):1000-28. doi: 10.1037/a0029924. Epub 2012 Sep 3.
3
The root of all value: a neural common currency for choice.
Curr Opin Neurobiol. 2012 Dec;22(6):1027-38. doi: 10.1016/j.conb.2012.06.001. Epub 2012 Jul 3.
4
There are at least two kinds of probability matching: evidence from a secondary task.
Cognition. 2011 Feb;118(2):274-9. doi: 10.1016/j.cognition.2010.11.009. Epub 2010 Dec 8.
5
Separate valuation subsystems for delay and effort decision costs.
J Neurosci. 2010 Oct 20;30(42):14080-90. doi: 10.1523/JNEUROSCI.2752-10.2010.
6
Synaptic computation underlying probabilistic inference.
Nat Neurosci. 2010 Jan;13(1):112-9. doi: 10.1038/nn.2450. Epub 2009 Dec 13.
7
Effort-based cost-benefit valuation and the human brain.
J Neurosci. 2009 Apr 8;29(14):4531-41. doi: 10.1523/JNEUROSCI.4515-08.2009.
8
Decision theory: what "should" the nervous system do?
Science. 2007 Oct 26;318(5850):606-10. doi: 10.1126/science.1142998.
9
Choice in free-ranging wild pigeons.
Science. 1974 Jul 5;185(4145):78-9. doi: 10.1126/science.185.4145.78.
10
Operant matching is a generic outcome of synaptic plasticity based on the covariance between reward and neural activity.
Proc Natl Acad Sci U S A. 2006 Oct 10;103(41):15224-9. doi: 10.1073/pnas.0505220103. Epub 2006 Sep 28.

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