The effect of novelty on reinforcement learning

A Houillon; R C Lorenz; W Boehmer; M A Rapp; A Heinz; J Gallinat; K Obermayer

doi:10.1016/B978-0-444-62604-2.00021-6

The effect of novelty on reinforcement learning

Standard

The effect of novelty on reinforcement learning. / Houillon, A; Lorenz, R C; Boehmer, W; Rapp, M A; Heinz, A; Gallinat, J; Obermayer, K.

In: PROG BRAIN RES, Vol. 202, 01.01.2013, p. 415-39.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Houillon, A, Lorenz, RC, Boehmer, W, Rapp, MA, Heinz, A, Gallinat, J & Obermayer, K 2013, 'The effect of novelty on reinforcement learning', PROG BRAIN RES, vol. 202, pp. 415-39. https://doi.org/10.1016/B978-0-444-62604-2.00021-6

APA

Houillon, A., Lorenz, R. C., Boehmer, W., Rapp, M. A., Heinz, A., Gallinat, J., & Obermayer, K. (2013). The effect of novelty on reinforcement learning. PROG BRAIN RES, 202, 415-39. https://doi.org/10.1016/B978-0-444-62604-2.00021-6

Vancouver

Houillon A, Lorenz RC, Boehmer W, Rapp MA, Heinz A, Gallinat J et al. The effect of novelty on reinforcement learning. PROG BRAIN RES. 2013 Jan 1;202:415-39. https://doi.org/10.1016/B978-0-444-62604-2.00021-6

Bibtex

@article{5587732550454ab6a8d6698b4b767e03,

title = "The effect of novelty on reinforcement learning",

abstract = "Recent research suggests that novelty has an influence on reward-related learning. Here, we showed that novel stimuli presented from a pre-familiarized category can accelerate or decelerate learning of the most rewarding category, depending on the condition. The extent of this influence depended on the individual trait of novelty seeking. Different reinforcement learning models were developed to quantify subjects' choices. We introduced a bias parameter to model explorative behavior toward novel stimuli and characterize individual variation in novelty response. The theoretical framework allowed us to test different assumptions, concerning the motivational value of novelty. The best fitting-model combined all novelty components and had a significant positive correlation with both the experimentally measured novelty bias and the independent novelty-seeking trait. Altogether, we have not only shown that novelty by itself enhances behavioral responses underlying reward processing, but also that novelty has a direct influence on reward-dependent learning processes, consistently with computational predictions.",

keywords = "Adult, Bias (Epidemiology), Computer Simulation, Decision Making, Exploratory Behavior, Female, Humans, Individuality, Male, Markov Chains, Models, Neurological, Models, Psychological, Probability Learning, Reinforcement (Psychology), Young Adult",

author = "A Houillon and Lorenz, {R C} and W Boehmer and Rapp, {M A} and A Heinz and J Gallinat and K Obermayer",

year = "2013",

month = jan,

day = "1",

doi = "10.1016/B978-0-444-62604-2.00021-6",

language = "English",

volume = "202",

pages = "415--39",

journal = "PROG BRAIN RES",

issn = "0079-6123",

publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - The effect of novelty on reinforcement learning

AU - Houillon, A

AU - Lorenz, R C

AU - Boehmer, W

AU - Rapp, M A

AU - Heinz, A

AU - Gallinat, J

AU - Obermayer, K

PY - 2013/1/1

Y1 - 2013/1/1

N2 - Recent research suggests that novelty has an influence on reward-related learning. Here, we showed that novel stimuli presented from a pre-familiarized category can accelerate or decelerate learning of the most rewarding category, depending on the condition. The extent of this influence depended on the individual trait of novelty seeking. Different reinforcement learning models were developed to quantify subjects' choices. We introduced a bias parameter to model explorative behavior toward novel stimuli and characterize individual variation in novelty response. The theoretical framework allowed us to test different assumptions, concerning the motivational value of novelty. The best fitting-model combined all novelty components and had a significant positive correlation with both the experimentally measured novelty bias and the independent novelty-seeking trait. Altogether, we have not only shown that novelty by itself enhances behavioral responses underlying reward processing, but also that novelty has a direct influence on reward-dependent learning processes, consistently with computational predictions.

AB - Recent research suggests that novelty has an influence on reward-related learning. Here, we showed that novel stimuli presented from a pre-familiarized category can accelerate or decelerate learning of the most rewarding category, depending on the condition. The extent of this influence depended on the individual trait of novelty seeking. Different reinforcement learning models were developed to quantify subjects' choices. We introduced a bias parameter to model explorative behavior toward novel stimuli and characterize individual variation in novelty response. The theoretical framework allowed us to test different assumptions, concerning the motivational value of novelty. The best fitting-model combined all novelty components and had a significant positive correlation with both the experimentally measured novelty bias and the independent novelty-seeking trait. Altogether, we have not only shown that novelty by itself enhances behavioral responses underlying reward processing, but also that novelty has a direct influence on reward-dependent learning processes, consistently with computational predictions.

KW - Adult

KW - Bias (Epidemiology)

KW - Computer Simulation

KW - Decision Making

KW - Exploratory Behavior

KW - Female

KW - Humans

KW - Individuality

KW - Male

KW - Markov Chains

KW - Models, Neurological

KW - Models, Psychological

KW - Probability Learning

KW - Reinforcement (Psychology)

KW - Young Adult

U2 - 10.1016/B978-0-444-62604-2.00021-6

DO - 10.1016/B978-0-444-62604-2.00021-6

M3 - SCORING: Journal article

C2 - 23317843

VL - 202

SP - 415

EP - 439

JO - PROG BRAIN RES

JF - PROG BRAIN RES

SN - 0079-6123

ER -