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2015


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When to use which heuristic: A rational solution to the strategy selection problem

Lieder, F., Griffiths, T. L.

In Proceedings of the 37th Annual Conference of the Cognitive Science Society, 2015 (inproceedings)

Abstract
The human mind appears to be equipped with a toolbox full of cognitive strategies, but how do people decide when to use which strategy? We leverage rational metareasoning to derive a rational solution to this problem and apply it to decision making under uncertainty. The resulting theory reconciles the two poles of the debate about human rationality by proposing that people gradually learn to make rational use of fallible heuristics. We evaluate this theory against empirical data and existing accounts of strategy selection (i.e. SSL and RELACS). Our results suggest that while SSL and RELACS can explain people's ability to adapt to homogeneous environments in which all decision problems are of the same type, rational metareasoning can additionally explain people's ability to adapt to heterogeneous environments and flexibly switch strategies from one decision to the next.

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link (url) Project Page [BibTex]

2015


link (url) Project Page [BibTex]


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Children and Adults Differ in their Strategies for Social Learning

Lieder, F., Sim, Z. L., Hu, J. C., Griffiths, T. L., Xu, F.

In Proceedings of the 37th Annual Conference of the Cognitive Science Society, 2015 (inproceedings)

Abstract
Adults and children rely heavily on other people’s testimony. However, domains of knowledge where there is no consensus on the truth are likely to result in conflicting testimonies. Previous research has demonstrated that in these cases, learners look towards the majority opinion to make decisions. However, it remains unclear how learners evaluate social information, given that considering either the overall valence, or the number of testimonies, or both may lead to different conclusions. We therefore formalized several social learning strategies and compared them to the performance of adults and children. We find that children use different strategies than adults. This suggests that the development of social learning may involve the acquisition of cognitive strategies.

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link (url) [BibTex]

link (url) [BibTex]


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Learning from others: Adult and child strategies in assessing conflicting ratings

Hu, J., Lieder, F., Griffiths, T. L., Xu, F.

In Biennial Meeting of the Society for Research in Child Development, Philadelphia, Pennsylvania, USA, 2015 (inproceedings)

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[BibTex]

[BibTex]


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Utility-weighted sampling in decisions from experience

Lieder, F., Griffiths, T. L., Hsu, M.

In The 2nd Multidisciplinary Conference on Reinforcement Learning and Decision Making, 2015 (inproceedings)

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[BibTex]

[BibTex]

2014


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Algorithm selection by rational metareasoning as a model of human strategy selection

Lieder, F., Plunkett, D., Hamrick, J. B., Russell, S. J., Hay, N. J., Griffiths, T. L.

In Advances in Neural Information Processing Systems 27, 2014 (inproceedings)

Abstract
Selecting the right algorithm is an important problem in computer science, because the algorithm often has to exploit the structure of the input to be efficient. The human mind faces the same challenge. Therefore, solutions to the algorithm selection problem can inspire models of human strategy selection and vice versa. Here, we view the algorithm selection problem as a special case of metareasoning and derive a solution that outperforms existing methods in sorting algorithm selection. We apply our theory to model how people choose between cognitive strategies and test its prediction in a behavioral experiment. We find that people quickly learn to adaptively choose between cognitive strategies. People's choices in our experiment are consistent with our model but inconsistent with previous theories of human strategy selection. Rational metareasoning appears to be a promising framework for reverse-engineering how people choose among cognitive strategies and translating the results into better solutions to the algorithm selection problem.

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Project Page [BibTex]

2014


Project Page [BibTex]


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Self-Exploration of the Stumpy Robot with Predictive Information Maximization

Martius, G., Jahn, L., Hauser, H., V. Hafner, V.

In Proc. From Animals to Animats, SAB 2014, 8575, pages: 32-42, LNCS, Springer, 2014 (inproceedings)

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[BibTex]

[BibTex]


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The high availability of extreme events serves resource-rational decision-making

Lieder, F., Hsu, M., Griffiths, T. L.

In Proceedings of the 36th Annual Conference of the Cognitive Science Society, 2014 (inproceedings)

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[BibTex]

[BibTex]


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Layers of Abstraction: (Neuro)computational models of learning local and global statistical regularities

Diaconescu, A., Lieder, F., Mathys, C., Stephan, K. E.

In 20th Annual Meeting of the Organization for Human Brain Mapping, 2014 (inproceedings)

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[BibTex]

[BibTex]

2007


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Guided Self-organisation for Autonomous Robot Development

Martius, G., Herrmann, J. M., Der, R.

In Advances in Artificial Life 9th European Conference, ECAL 2007, 4648, pages: 766-775, LNCS, Springer, 2007 (inproceedings)

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[BibTex]

2007


[BibTex]