scholarly journals Reward-Rate Maximization in Sequential Identification under a Stochastic Deadline

2013 ◽  
Vol 51 (4) ◽  
pp. 2922-2948 ◽  
Author(s):  
Savas Dayanik ◽  
Angela J. Yu
Keyword(s):  
Reward Rate ◽  
Rate Maximization ◽  
Reward Rate Maximization

Discarding optimality: Throwing out the baby with the bathwater?

2018 ◽  
Vol 41 ◽  
Author(s):  
Patrick Simen ◽  
Fuat Balcı
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Reward Rate ◽  
Perceptual Decision ◽  
Standard Observer ◽  
Rate Maximization ◽  
Reward Rate Maximization ◽  
Descriptive Standard ◽  
Observer Model

AbstractRahnev & Denison (R&D) argue against normative theories and in favor of a more descriptive “standard observer model” of perceptual decision making. We agree with the authors in many respects, but we argue that optimality (specifically, reward-rate maximization) has proved demonstrably useful as a hypothesis, contrary to the authors’ claims.

The Urge to Decide and Act: Implications for Brain Function and Dysfunction

2019 ◽  
Vol 25 (5) ◽  
pp. 491-511 ◽  
Author(s):  
Matthew A. Carland ◽  
David Thura ◽  
Paul Cisek
Keyword(s):  
Action Execution ◽  
Behavioral Measures ◽  
Reward Rate ◽  
Rate Maximization ◽  
Individual Trait ◽  
Wide Range ◽  
Neurophysiological Data ◽  
Reward Rate Maximization ◽  
Potential Link ◽  
Cortical Regions

Humans and other animals are motivated to act so as to maximize their subjective reward rate. Here, we propose that reward rate maximization is accomplished by adjusting a context-dependent “urgency signal,” which influences both the commitment to a developing action choice and the vigor with which the ensuing action is performed. We review behavioral and neurophysiological data suggesting that urgency is controlled by projections from the basal ganglia to cerebral cortical regions, influencing neural activity related to decision making as well as activity related to action execution. We also review evidence suggesting that different individuals possess specific policies for adjusting their urgency signal to particular contextual variables, such that urgency constitutes an individual trait which jointly influences a wide range of behavioral measures commonly related to the overall quality and hastiness of one’s decisions and actions. Consequently, we argue that a central mechanism for reward rate maximization provides a potential link between personality traits such as impulsivity, as well as some of the motivation-related symptomology of clinical disorders such as depression and Parkinson’s disease.

Artificial intelligence techniques for rate maximization in interference channels

2021 ◽  
pp. 101294
Author(s):  
Zain Ali ◽  
Wasay Farooq ◽  
Wali Ullah Khan ◽  
Mahmood Qureshi ◽  
Guftaar Ahmad Sardar Sidhu
Keyword(s):  
Artificial Intelligence ◽  
Interference Channels ◽  
Artificial Intelligence Techniques ◽  
Rate Maximization
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