scholarly journals Minimizing the Cost of Guessing Games

2018 ◽  
Vol 15 (2) ◽  
Author(s):  
David Clark ◽  
Lindsay Czap
Keyword(s):  
Cost Function ◽  
Coding Theory ◽  
Minimum Cost ◽  
Error Correcting Codes ◽  
Triple Systems ◽  
Pairwise Balanced Designs ◽  
Constant Cost ◽  
Balanced Designs ◽  
The Cost ◽  
Guessing Games

A two-player “guessing game” is a game in which the first participant, the “Responder,” picks a number from a certain range. Then, the second participant, the “Questioner,” asks only yes-or-no questions in order to guess the number. In this paper, we study guessing games with lies and costs. In particular, the Responder is allowed to lie in one answer, and the Questioner is charged a cost based on the content of each question. Guessing games with lies are closely linked to error correcting codes, which are mathematical objects that allow us to detect an error in received information and correct these errors. We will give basic definitions in coding theory and show how error correcting codes allow us to still guess the correct number even if one lie is involved. We will additionally seek to minimize the total cost of our games. We will provide explicit constructions, for any cost function, for games with the minimum possible cost and an unlimited number of questions. We also find minimum cost games for games with a restricted number of questions and a constant cost function. KEYWORDS: Ulam’s Game; Guessing Games With Lies; Error Correcting Codes; Pairwise Balanced Designs; Steiner Triple Systems

Research on the Method of Reliability Allocation of Diesel Engine Base on the Cost Function

2012 ◽  
Vol 271-272 ◽  
pp. 1115-1120
Author(s):  
Jia Li ◽  
Ji Ze Guo ◽  
Hai Qing Zhou ◽  
You Wen Wei
Keyword(s):  
Diesel Engine ◽  
Cost Function ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Minimum Cost ◽  
Copula Function ◽  
Reliability Allocation ◽  
Cost Coefficient ◽  
Set Up ◽  
The Cost

In this paper, cost coefficient is introduced by using the technology of FMECA and FTA, and the DM model is proposed, the parameters of cost function are determined by applying the comprehensive evaluation method, the system reliability correlation model is set up by using copula function. the model is nonlinear programming, and the minimum cost is the goal of the model. The reliability allocation for diesel engine is completed by use of genetic algorithm. Finally, the feasibility and effectiveness of the model are verified through example.

scholarly journals A Node-Charge Graph-Based Online Carshare Rebalancing Policy with Capacitated Electric Charging

2021 ◽  
Author(s):  
Theodoros P. Pantelidis ◽  
Li Li ◽  
Tai-Yu Ma ◽  
Joseph Y. J. Chow ◽  
Saif Eddin G. Jabari
Keyword(s):  
New York ◽  
Cost Function ◽  
Minimum Cost ◽  
Charging Station ◽  
Location Data ◽  
Feasible Solutions ◽  
The Cost ◽  
Flow Conservation ◽  
Charging Stations ◽  
Station Location

Viability of electric car-sharing operations depends on rebalancing algorithms. Earlier methods in the literature suggest a trend toward nonmyopic algorithms using queueing principles. We propose a new rebalancing policy using cost function approximation. The cost function is modeled as a p-median relocation problem with minimum cost flow conservation and path-based charging station capacities on a static node-charge graph structure. The cost function is NP complete, so a heuristic is proposed that ensures feasible solutions that can be solved in an online system. The algorithm is validated in a case study of electric carshare in Brooklyn, New York, with demand data shared from BMW ReachNow operations in September 2017 (262 vehicle fleet, 231 pickups per day, and 303 traffic analysis zones) and charging station location data (18 charging stations with four-port capacities). The proposed nonmyopic rebalancing heuristic reduces the cost increase compared with myopic rebalancing by 38%. Other managerial insights are further discussed.

scholarly journals The reserve of joint torque determines movement coordination

2021 ◽  
Author(s):  
Germain Faity ◽  
Denis Mottet ◽  
Simon Pla ◽  
Jérôme Froger
Keyword(s):  
Optimal Control ◽  
Cost Function ◽  
Degrees Of Freedom ◽  
Minimum Cost ◽  
Joint Torque ◽  
Movement Coordination ◽  
Trunk Motion ◽  
Additional Load ◽  
The Cost ◽  
Healthy Participants

AbstractHumans coordinate biomechanical degrees of freedom to perform tasks at minimum cost. When reaching a target from a seated position, the trunk-arm-forearm coordination moves the hand to the well-defined spatial goal, while typically minimising hand jerk and trunk motion. However, due to fatigue or stroke, people visibly move the trunk more, and it is unclear what cost can account for this. Here we show that people recruit their trunk when the torque at the shoulder is too close to the maximum. We asked 26 healthy participants to reach a target while seated and we found that the trunk contribution to hand displacement increases from 11% to 27% when an additional load is handled. By flexing and rotating the trunk, participants spontaneously increase the reserve of anti-gravitational torque at the shoulder from 25% to 40% of maximal voluntary torque. Our findings provide hints on how to include the reserve of torque in the cost function of optimal control models of human coordination in healthy fatigued persons or in stroke victims.

scholarly journals OPP approach for multi degree of freedom robotic arm Based on Kinematics and Dynamics of Robot

2015 ◽  
Vol 4 (4) ◽  
pp. 284
Author(s):  
Praneet Dutta ◽  
Rashmi Ranjan Das ◽  
Rupali Mathur ◽  
Deepika Rani Sona
Keyword(s):  
Optimal Control ◽  
Cost Function ◽  
Minimum Principle ◽  
Equations Of Motion ◽  
Optimal Path ◽  
Minimum Cost ◽  
Simulation Software ◽  
Degree Of Freedom ◽  
The Cost ◽  
Joint Velocity

This paper deals with the trajectory and path generation of the industrial manipulator. The trajectory is obtained using the equations of motion and also the optimal path planning (OPP) approach under kinodynamic constraints. The optimal control problem is defined for the minimum cost function and to obtain the necessary conditions. Here we have used pontrygain’s minimum principle to obtain the limiting value of joint angle and also  the joint velocity and torque. In this paper we have used the “Two degree of freedom (DOF) manipulator” for analysis and designing the optimal control for multi link and multi degree of freedom manipulator. For analysis purposes,  simulation software has been used to formulate the trajectory and minimize the cost function involved.

scholarly journals The reserve of joint torque determines movement coordination

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germain Faity ◽  
Denis Mottet ◽  
Simon Pla ◽  
Jérôme Froger
Keyword(s):  
Optimal Control ◽  
Cost Function ◽  
Degrees Of Freedom ◽  
Minimum Cost ◽  
Joint Torque ◽  
Movement Coordination ◽  
Trunk Motion ◽  
Additional Load ◽  
The Cost ◽  
Healthy Participants

AbstractHumans coordinate biomechanical degrees of freedom to perform tasks at minimum cost. When reaching a target from a seated position, the trunk-arm-forearm coordination moves the hand to the well-defined spatial goal, while typically minimising hand jerk and trunk motion. However, due to fatigue or stroke, people visibly move the trunk more, and it is unclear what cost can account for this. Here we show that people recruit their trunk when the torque at the shoulder is too close to the maximum. We asked 26 healthy participants to reach a target while seated and we found that the trunk contribution to hand displacement increases from 11 to 27% when an additional load is handled. By flexing and rotating the trunk, participants spontaneously increase the reserve of anti-gravitational torque at the shoulder from 25 to 40% of maximal voluntary torque. Our findings provide hints on how to include the reserve of torque in the cost function of optimal control models of human coordination in healthy fatigued persons or in stroke victims.

scholarly journals MINIMUM COST TOPOLOGICAL ORDERING

2018 ◽  
Author(s):  
Thinh D. Nguyen
Keyword(s):  
Cost Function ◽  
Directed Graph ◽  
Minimum Cost ◽  
Np Hard ◽  
The Cost

We are given an $n$ vertex directed graph $G=(V,E)$ and also given a cost function $c:V\times [n]\to \mathbb{R}$. Consider a topological ordering of the vertices, $v_1,\ldots,v_n$, the cost of the ordering is $\sum_{i=1}^n c(v_i,i)$. We shall prove that finding the minimum cost topological ordering is $\mathrm{NP}$-hard.

A generalized fuzzy cost efficiency model

2020 ◽  
Vol 54 (6) ◽  
pp. 1775-1791
Author(s):  
Nazila Aghayi ◽  
Samira Salehpour
Keyword(s):  
Cost Efficiency ◽  
Minimum Cost ◽  
Extensive Literature ◽  
Data Envelopment ◽  
Fuzzy Environment ◽  
Decision Making Unit ◽  
Production Possibility Set ◽  
Fuzzy Cost ◽  
The Cost ◽  
Generalized Cost

The concept of cost efficiency has become tremendously popular in data envelopment analysis (DEA) as it serves to assess a decision-making unit (DMU) in terms of producing minimum-cost outputs. A large variety of precise and imprecise models have been put forward to measure cost efficiency for the DMUs which have a role in constructing the production possibility set; yet, there’s not an extensive literature on the cost efficiency (CE) measurement for sample DMUs (SDMUs). In an effort to remedy the shortcomings of current models, herein is introduced a generalized cost efficiency model that is capable of operating in a fuzzy environment-involving different types of fuzzy numbers-while preserving the Farrell’s decomposition of cost efficiency. Moreover, to the best of our knowledge, the present paper is the first to measure cost efficiency by using vectors. Ultimately, a useful example is provided to confirm the applicability of the proposed methods.

Main approaches to estimating the cost of shareholder equity of oil and gas producers

2020 ◽  
Vol 26 (3) ◽  
pp. 685-697
Author(s):  
O.V. Shimko
Keyword(s):  
Oil And Gas ◽  
Oil Prices ◽  
Minimum Cost ◽  
Free Cash Flow ◽  
Annual Reports ◽  
Comparative Approach ◽  
Economic Activities ◽  
Advantages And Disadvantages ◽  
Oil And Gas Producers ◽  
The Cost

Subject. The study analyzes generally accepted approaches to assessing the value of companies on the basis of financial statement data of ExxonMobil, Chevron, ConocoPhillips, Occidental Petroleum, Devon Energy, Anadarko Petroleum, EOG Resources, Apache, Marathon Oil, Imperial Oil, Suncor Energy, Husky Energy, Canadian Natural Resources, Royal Dutch Shell, Gazprom, Rosneft, LUKOIL, and others, for 1999—2018. Objectives. The aim is to determine the specifics of using the methods of cost, DFC, and comparative approaches to assessing the value of share capital of oil and gas companies. Methods. The study employs methods of statistical analysis and generalization of materials of scientific articles and official annual reports on the results of financial and economic activities of the largest public oil and gas corporations. Results. Based on the results of a comprehensive analysis, I identified advantages and disadvantages of standard approaches to assessing the value of oil and gas producers. Conclusions. The paper describes pros and cons of the said approaches. For instance, the cost approach is acceptable for assessing the minimum cost of small companies in the industry. The DFC-based approach complicates the reliability of medium-term forecasts for oil prices due to fluctuations in oil prices inherent in the industry, on which the net profit and free cash flow of companies depend to a large extent. The comparative approach enables to quickly determine the range of possible value of the corporation based on transactions data and current market situation.

scholarly journals An Adaptive Optimization Method Based on Learning Rate Schedule for Neural Networks

2021 ◽  
Vol 11 (2) ◽  
pp. 850
Author(s):  
Dokkyun Yi ◽  
Sangmin Ji ◽  
Jieun Park
Keyword(s):  
Artificial Intelligence ◽  
Cost Function ◽  
Numerical Experiments ◽  
Global Minimum ◽  
Optimization Method ◽  
Learning Method ◽  
Adaptive Optimization ◽  
The Cost ◽  
Proof Of Convergence ◽  
Learning Data

Artificial intelligence (AI) is achieved by optimizing the cost function constructed from learning data. Changing the parameters in the cost function is an AI learning process (or AI learning for convenience). If AI learning is well performed, then the value of the cost function is the global minimum. In order to obtain the well-learned AI learning, the parameter should be no change in the value of the cost function at the global minimum. One useful optimization method is the momentum method; however, the momentum method has difficulty stopping the parameter when the value of the cost function satisfies the global minimum (non-stop problem). The proposed method is based on the momentum method. In order to solve the non-stop problem of the momentum method, we use the value of the cost function to our method. Therefore, as the learning method processes, the mechanism in our method reduces the amount of change in the parameter by the effect of the value of the cost function. We verified the method through proof of convergence and numerical experiments with existing methods to ensure that the learning works well.

A claims problem approach to the cost allocation of a minimum cost spanning tree

2021 ◽  
Author(s):  
José-Manuel Giménez-Gómez ◽  
Josep E. Peris ◽  
Begoña Subiza
Keyword(s):  
Spanning Tree ◽  
Cost Allocation ◽  
Minimum Cost ◽  
Claims Problem ◽  
The Cost
Sign in / Sign up

Export Citation Format

Share Document