scholarly journals One problem, too many solutions: How costly is honest signalling of need?

2017 ◽  
Author(s):  
Szabolcs Számadó ◽  
Dániel Czégel ◽  
István Zachar

AbstractThe “cost of begging” is a prominent prediction of costly signalling theory, suggesting that offspring begging has to be costly in order to be honest. More specifically, it predicts that there is a single cost function for the offspring (depending on e.g. offspring quality) that maintains honesty and it must be proportional to parent’s fitness loss. Here we show another interpretation of the cost. We demonstrate that cost, proportional to the fitness gain of the offspring, also results in honest signalling. Since the loss of the parent does not necessarily coincide with the gain of the offspring, it is provable that any linear combination of the two cost functions (one proportional to parent’s loss, one to offspring’s gain) also leads to honest signalling. Our results, applied for a specific model, support the previous general conclusion that signalling games have different cost functions for different equilibria. Consequently, costly signalling theory cannot predict a unique equilibrium cost in signalling games especially in case of parent-offspring conflicts. As an important consequence, any measured equilibrium cost in real cases has to be compared both to the parent’s fitness loss and to the offspring’s fitness gain in order to provide meaningfully interpretation.

2018 ◽  
Vol 11 (1) ◽  
pp. 429-439 ◽  
Author(s):  
Marcin L. Witek ◽  
Michael J. Garay ◽  
David J. Diner ◽  
Michael A. Bull ◽  
Felix C. Seidel

Abstract. A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, “best estimate” AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.


Author(s):  
Thomas Smith ◽  
Panorios Benardos ◽  
David Branson

The aim of this research is to develop a framework to allow efficient human robot collaboration on manufacturing assembly tasks based on cost functions that quantify capabilities and performance of each element in a system and enable their efficient evaluation. A proposed cost function format is developed along with initial development of two example cost function variables, completion time and fatigue, obtained as each worker is completing assembly tasks. The cost function format and example variables were tested with two example tasks utilizing an ABB YuMi Robot in addition to a simulated human worker under various levels of fatigue. The total costs produced clearly identified the best worker to complete each task with these costs also clearly indicating when a human worker is fatigued to a greater or lesser degree than expected.


2004 ◽  
Vol 19 (3) ◽  
pp. 345-358 ◽  
Author(s):  
Shane S. Dikolli ◽  
Karen L. Sedatole

This case provides the opportunity to use various empirical techniques (i.e., high-low method, simple regression, and multiple regression) in the estimation of cost functions. The case uses the airline industry as the setting for this analysis and, in particular, focuses on the ef forts of Delta Airlines to plan for salaries, the cost category that dominates its income statement. The case provides the data and the opportunity to learn the details of cost function estimation, but more importantly, it provides a rich setting in which issues related to the interpretation of these cost functions can be discussed. Finally, the entry of Delta into the low-cost carrier segment with its formation of Song provides a unique opportunity to think about how the cost function of an established full-service airline compares to that of a low-fare startup. Data from successful newcomer JetBlue is used to illustrate these differences. More generally, the case shows how the use of historical costs and cost estimation techniques can facilitate decision making about entry into new product markets.


2013 ◽  
Vol 10 (87) ◽  
pp. 20130469 ◽  
Author(s):  
Frazer Meacham ◽  
Aaron Perlmutter ◽  
Carl T. Bergstrom

Costly signalling theory is commonly invoked as an explanation for how honest communication can be stable when interests conflict. However, the signal costs predicted by costly signalling models often turn out to be unrealistically high. These models generally assume that signal cost is determinate. Here, we consider the case where signal cost is instead stochastic. We examine both discrete and continuous signalling games and show that, under reasonable assumptions, stochasticity in signal costs can decrease the average cost at equilibrium for all individuals. This effect of stochasticity for decreasing signal costs is a fundamental mechanism that probably acts in a wide variety of circumstances.


2017 ◽  
Vol 36 (13-14) ◽  
pp. 1474-1488 ◽  
Author(s):  
Peter Englert ◽  
Ngo Anh Vien ◽  
Marc Toussaint

Inverse optimal control (IOC) assumes that demonstrations are the solution to an optimal control problem with unknown underlying costs, and extracts parameters of these underlying costs. We propose the framework of inverse Karush–Kuhn–Tucker (KKT), which assumes that the demonstrations fulfill the KKT conditions of an unknown underlying constrained optimization problem, and extracts parameters of this underlying problem. Using this we can exploit the latter to extract the relevant task spaces and parameters of a cost function for skills that involve contacts. For a typical linear parameterization of cost functions this reduces to a quadratic program, ensuring guaranteed and very efficient convergence, but we can deal also with arbitrary non-linear parameterizations of cost functions. We also present a non-parametric variant of inverse KKT that represents the cost function as a functional in reproducing kernel Hilbert spaces. The aim of our approach is to push learning from demonstration to more complex manipulation scenarios that include the interaction with objects and therefore the realization of contacts/constraints within the motion. We demonstrate the approach on manipulation tasks such as sliding a box, closing a drawer and opening a door.


Author(s):  
Aleksander Alekseev ◽  

The control problem of a multi-criteria object is considered. Controlled object that has several criteria that are significant for a decision maker. Each criterion characterizes a control object in terms of a particular result of activity or an efficiency indicator. To evaluate the effectiveness of the functioning of the managed facility as a whole, the rating matrix mechanism is used, taking into account all the criteria in the complex. The optimal control problem is formulated as a search for the values ​​of aggregated criteria that provide a given value of a complex indicator with minimal costs for providing values ​​of particular criteria. The generalized cost function was reduced to an equation with one variable. The analytical equation of the level line of the indicator aggregated as a result of the convolution of two criteria is obtained. The line equation is found for an arbitrary binary convolution matrix, including the elements of which are given continuous values. It is shown that the objective function is reduced to a fourth-order polynomial, which can be analytically solved using the Ferrari or Descartes-Euler methods. It is shown that the task of searching for the values of two particular criteria describing the state of the control object for which the complex indicator calculated using the additive-multiplicative approach to complex assessment is equal to the given value and the costs for their provision are minimal, has a solution in general form for arbitrary nondecreasing convolution matrix of two criteria. Particular solutions to the control problem are found using costly functions, which are the inverse function of the Cobb-Douglas production function. It was shown that the cost function of the aggregate indicator has additional terms and is described by an algebraic equation with nonzero coefficients for variables and an additional constant. Based on what it was concluded that the cost functions, which are the inverse function e of the Cobb-Douglas production function, can be applied to control objects that have only two criteria. A similar formulation of the control problem for an arbitrary non-decreasing convolution matrix of two criteria is considered when using the additive-multiplicative approach to aggregation and when using cost functions described by a second-order algebraic equation in general form. As a result of the study, it is shown that the form of the cost function for the aggregated indicator is preserved. Thus, using cost functions in the form of second-order equations, the control problem has a solution in the general form for any number of criteria.


2017 ◽  
Author(s):  
Marcin L. Witek ◽  
Michael J. Garay ◽  
David J. Diner ◽  
Michael A. Bull ◽  
Felix C. Seidel

Abstract. A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR’s aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous Version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture, then used a combination of these values to compute the final, best estimate AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of a) the absolute values of the cost functions for each aerosol mixture, b) the widths of the cost function distributions as a function of AOD, and c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on arbitrary thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new Aerosol Retrieval Confidence Index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥ 0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.


Author(s):  
Carlo L. Bottasso ◽  
Alessandro Croce ◽  
Stefano Sartirana ◽  
Boris I. Prilutsky

We propose a computational procedure for inferring the cost functions that, according to the Principle of Optimality, underlie experimentally observed motor strategies. This work tries to overcome the need to hypothesize the cost functions, extracting this non-directly observable information from experimental data. Optimality criteria of observed motor tasks are here indirectly derived using: a) a mathematical model of the bio-system; and b) a parametric mathematical model of the possible cost functions, i.e. a search space constructed in such a way as to presumably contain the unknown function that was used by the bio-system in the given motor task of interest. The cost function that best matches the experimental data is identified within the search space by solving a nested optimization problem. This problem can be recast as a non-linear programming problem and therefore solved using standard techniques. The proposed methodology is tested on representative examples.


Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1947
Author(s):  
Giacomo Palmieri ◽  
Monica Tiboni ◽  
Giovanni Legnani

The article presents the study of the pedalling rates obtained by minimizing a cost function based on a kinetic approach and which can be estimated with more easily achievable experimental data as input than other cost functions. Simulations based on data available in the literature were used to compare the cadences obtained by minimizing well-known joint moment-based cost functions and the proposed cost function. The influence of the power output and of the body mass index on the pedalling rates that minimize the cost function was investigated. Experimental tests performed by four competitive cyclists in the field were used as comparison for the results based on simulations. From simulations emerged that results obtained with the cost function proposed in this work were similar to those based on the absolute average joint moments. We found that the upper limit of the more convenient pedalling rate range decreases linearly with the body mass index, while it increases non-linearly with power output. Furthermore, a polynomial regression of the correlation of the pedalling rate obtained through the method and body mass index and power was found. Experimental results confirmed that the proposed model, finding an approximation of the minimum of muscular effort (not including negative muscular work), is able to estimate the upper limit of an optimal range of cadence. All tested cyclists freely choose to pedal at a cadence under this limit.


2018 ◽  
Vol 185 ◽  
pp. 00033 ◽  
Author(s):  
Chia-Sheng Tu ◽  
Hsi-Shan Huang ◽  
Ming-Tang Tsai ◽  
Fu-Sheng Cheng

Dynamic economic dispatch is to minimize the cost of power production of all the participating generators over a time horizon of 24 hours in one day. The dynamic economic dispatch with non-smooth cost functions, for which is formulated the optimal dispatch model of generations by considering the ramp up/down scheduling of power. This paper presents a Bee Colony Optimization (BCO) that applies the Taguchi Method (TM) to solve the Dynamic Economic Dispatch problem. The Taguchi method that involves the use of orthogonal arrays in estimating of the non-smooth cost function and Bee Colony Optimization is used to find the objective function under the operational of system constraints. The Taguchi method can global optimization for fast local convergence by minimizing the cost function in a few iterations. The effectiveness and efficiency of the TM-BCO is demonstrated by using a 10 unit of IEEE case with non-smooth fuel cost functions and is more effective than other previously developed algorithms. Moreover, the proposed approach presents significant computational benefits than traditional random search method especially for multi-unit systems with larger numbers of non-smooth cost functions and more complicated dynamic economic dispatch.


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