scholarly journals Optimal Response Vigor and Choice Under Non-stationary Outcome Values

2017 ◽  
Author(s):  
Amir Dezfouli ◽  
Bernard W. Balleine ◽  
Richard Nock
Keyword(s):  
Optimal Control ◽  
Quantitative Analysis ◽  
Response Rate ◽  
Two Dimensions ◽  
Probability Matching ◽  
Optimal Response ◽  
Session Duration ◽  
Control Framework ◽  
Experimental Protocols ◽  
Response Vigor

AbstractWithin a rational framework a decision-maker selects actions based on the reward-maximisation principle which stipulates they acquire outcomes with the highest values at the lowest cost. Action selection can be divided into two dimensions: selecting an action from several alternatives, and choosing its vigor, i.e., how fast the selected action should be executed. Both of these dimensions depend on the values of the outcomes, and these values are often affected as more outcomes are consumed, and so are the actions. Despite this, previous works have addressed the computational substrates of optimal actions only in the specific condition that the values of outcomes are constant, and it is still unknown what the optimal actions are when the values of outcomes are non-stationary. Here, based on an optimal control framework, we derive a computational model for optimal actions under non-stationary outcome values. The results imply that even when the values of outcomes are changing, the optimal response rate is constant rather than decreasing. This finding shows that, in contrast to previous theories, the commonly observed changes in the actions cannot be purely attributed to the changes in the outcome values. We then prove that this observation can be explained based on the uncertainty about temporal horizons; e.g., in the case of experimental protocols, the session duration. We further show that when multiple outcomes are available, the model explains probability matching as well as maximisation choice strategies. The model provides, therefore, a quantitative analysis of optimal actions and explicit predictions for future testing.

scholarly journals On the optimal response vigor and choice under variable motivational drives

2016 ◽  
Author(s):  
Amir Dezfouli
Keyword(s):  
Decision Maker ◽  
Response Rate ◽  
Selection Process ◽  
Optimal Choice ◽  
Two Dimensions ◽  
Experimental Conditions ◽  
Optimal Response ◽  
Conditioning Experiment ◽  
Control Framework ◽  
Response Vigor

Within a rational framework, a decision-maker selects actions based on the reward-maximisation principle, i.e., acquiring the highest amount of reward with the lowest cost. Action selection can be divided into two dimensions: (i) selecting an action among several alternatives, and (ii) choosing the response vigor, i.e., how fast the selected action should be executed. Previous works have addressed the computational substrates of such a selection process under the assumption that outcome values are stationary and do not change during the course of a session. This assumption does not hold when the motivational drive of the decision-maker is variable, because it leads to changes in the values of the outcomes, e.g., satiety decreases the value of the outcome. Here, we utilize an optimal control framework and derive the optimal choice and response vigor under different experimental conditions. The results imply that, in contrast to previous suggestions, even under conditions that the values of the outcomes are changing during the session, the optimal response rate in an instrumental conditioning experiment is a constant response rate rather than decreasing. Furthermore, we prove that the uncertainty of the decision-maker about the duration of the session explains the commonly observed decrease in response rates within a session. We also show that when the environment consists of multiple outcomes, the model explains probability matching as well as maximisation choice strategies. These results, therefore, provide a quantitative analysis of optimal choice and response vigor under variable motivational drive, and provide predictions for future testing.

An Economic Model Predictive Control Approach for Wind Power Smoothing and Tower Load Mitigation

2018 ◽  
Author(s):  
Mohamed M. Alhneaish ◽  
Mohamed L. Shaltout ◽  
Sayed M. Metwalli
Keyword(s):  
Optimal Control ◽  
Optimal Control Problem ◽  
Model Predictive Control ◽  
Wind Power ◽  
Predictive Control ◽  
Economic Model ◽  
Control Algorithm ◽  
Fatigue Load ◽  
Economic Model Predictive Control ◽  
Control Framework

An economic model predictive control framework is presented in this study for an integrated wind turbine and flywheel energy storage system. The control objective is to smooth wind power output and mitigate tower fatigue load. The optimal control problem within the model predictive control framework has been formulated as a convex optimal control problem with linear dynamics and convex constraints that can be solved globally. The performance of the proposed control algorithm is compared to that of a standard wind turbine controller. The effect of the proposed control actions on the fatigue loads acting on the tower and blades is studied. The simulation results, with various wind scenarios, showed the ability of the proposed control algorithm to achieve the aforementioned objectives in terms of smoothing output power and mitigating tower fatigue load at the cost of a minimal reduction of the wind energy harvested.

scholarly journals Predictive factors of response to 3rd dose of COVID-19 mRNA vaccine in kidney transplant recipients

2021 ◽  
Author(s):  
Xavier Charmetant ◽  
Maxime Espi ◽  
Thomas Barba ◽  
Anne Ovize ◽  
Emmanuel Morelon ◽  
...  
Keyword(s):  
Kidney Transplant ◽  
Response Rate ◽  
Individual Variability ◽  
Spike Protein ◽  
Receptor Binding Domain ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Optimal Response ◽  
The Third ◽  
Response Increase

AbstractOnly a minority of kidney transplant recipients (KTRs) develop protective neutralizing titers of anti-receptor binding domain of spike protein (RBD) IgG after two doses of mRNA COVID-19 vaccine. Administration of a third dose of mRNA vaccine to KTRs with sub-optimal response increase anti-RBD IgG titers but with high inter-individual variability. Patients with the higher response rate to the third dose of vaccine can be identified by the presence of low anti-RBD IgG titers and spike-specific CD4+ T cells in their circulation 14 days after the second dose.

A phase II open label, single arm study to evaluate the efficacy of pembrolizumab for leukoplakia.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. TPS10606-TPS10606
Author(s):  
Ashleigh Porter ◽  
Audrey J. Zeh ◽  
Thu Ly ◽  
Alyssa Serna ◽  
Arturo Villanueva ◽  
...  
Keyword(s):  
Clinical Response ◽  
Phase Ii ◽  
Response Rate ◽  
Two Dimensions ◽  
Premalignant Lesions ◽  
Clinical Response Rate ◽  
Clinical Impression ◽  
Severe Dysplasia ◽  
Open Label ◽  
Recurrence Rates

TPS10606 Background: The presence of pre-cancerous oral lesions such as leukoplakia or erythroleukoplakia are known risk factors for the development of squamous cell carcinoma of the head and neck (SCCHN), however preventative agents have not yet shown clinical benefit. The risk of malignant transformation varies but has been quoted as high as 36% in some studies. While the primary mode of treatment of these lesions is largely surgical, recurrence rates are high. Pembrolizumab is a potent and selective humanized monoclonal antibody that is designed to directly block the interaction between PD-1 and PD-L1 (as well as PD-L2) that is currently FDA-approved for treatment of SCCHN. We have hypothesized that the treatment of oral premalignant lesions with pembrolizumab would be an effective and well-tolerated strategy to prevent transformation to invasive cancer. Methods: This study is an open-label, phase II study that will accrue 26 patients with leukoplakia, erythroleukoplakia, or proliferative verrucous leukoplakia with documented moderate to severe dysplasia or carcinoma in situ to be treated with pembrolizumab 200mg every 3 weeks for a total of 6 months. Patients must have visible and measurable lesions that will be both photographed and measured in two dimensions at each visit from the start of treatment until 12 months post-enrollment. Biopsies will be required at diagnosis and following the final treatment, with an optional biopsy following cycle 2 and at progression of disease. Major exclusion criteria include patients with mild dysplasia or hyperplasia, prior chemotherapy, targeted small molecule therapy, or radiation therapy within 2 weeks of Day 1 of study, or patients with a known additional malignancy that is active. Patients will also be excluded if they have received anti-PD-1, anti-PD-L1 or anti-PD-L2 treatments in the past. The primary objective is clinical response rate at 6 months, and will be quantified as the percentage of patients with a complete response (CR) and partial response (PR) at 6 months. A CR is defined as complete resolution by visual inspection for 4 weeks of more and a PR is defined as 50% or greater reduction of the product of the 2 dimensions of a single lesions or the sum of all lesions. Progressive disease (PD) is defined as unequivocal increase (greater than or equal to 5mm in one dimension and greater than 20% increase) or the development of new lesions. Secondary objectives will include histologic response rate at 6 months, change in clinical impression based on photographs, clinical response rate at 9 and 12 months, and toxicity. Additional exploratory objectives will include PD-L1 expression in leukoplakia lesions as well as p16 expression, presence of tumor infiltrating lymphocytes, and immunohistochemical as well as RNA sequencing gene expression profiling which may allow for the identification of novel biomarkers. Enrollment began in June 2019 and is ongoing. Clinical trial information: NCT03603223 .

scholarly journals Optimal Control Approach to Lambert’s Problem and Gibbs’ Method

2020 ◽  
Vol 10 (7) ◽  
pp. 2419
Author(s):  
Minjeong Kim ◽  
Sungsu Park
Keyword(s):  
Optimal Control ◽  
Pseudospectral Method ◽  
Orbital Energy ◽  
Control Approach ◽  
Control Framework ◽  
Lambert’S Problem ◽  
Computation Algorithm ◽  
Lambert's Problem ◽  
Energy Computation ◽  
Optimal Control Approach

This paper presents the optimal control approach to solve both Lambert’s problem and Gibbs’ method, which are commonly used for preliminary orbit determination. Lambert’s problem is reinterpreted with Hamilton’s principle and is converted to an optimal control problem. Various extended Lambert’s problems are formulated by modifying the weighting and constraint settings within the optimal control framework. Furthermore, Gibbs’ method is also converted to an extended Lambert’s problem with two position vectors and one orbit energy with the help of the proposed orbital energy computation algorithm. The proposed extended Lambert’s problem and Gibbs’ method are numerically solved with the Lobatto pseudospectral method, and their accuracies are verified by numerical simulations.

Sign in / Sign up

Export Citation Format

Share Document