Evolved response thresholds generalize across problem instances for a deterministic-response multiagent system

2021 ◽  
Author(s):  
H. David Mathias ◽  
Annie S. Wu ◽  
Daniel Dang
Keyword(s):  
Multiagent System ◽  
Response Thresholds ◽  
Problem Instances

Division of Labor and Task Allocation

1999 ◽  
Author(s):  
Eric Bonabeau ◽  
Marco Dorigo ◽  
Guy Theraulaz
Keyword(s):  
Task Performance ◽  
Division Of Labor ◽  
Social Insects ◽  
Task Allocation ◽  
Multiagent System ◽  
Threshold Model ◽  
Response Threshold ◽  
Response Threshold Model ◽  
Response Thresholds ◽  
Colony Level

Many species of social insects have a division of labor. The resilience of task allocation exhibited at the colony level is connected to the elasticity of individual workers. The behavioral repertoire of workers can be stretched back and forth in response to perturbations. A model based on response thresholds connects individual-level plasticity with colony-level resiliency and can account for some important experimental results. Response thresholds refer to likelihood of reacting to task-associated stimuli. Low-threshold individuals perform tasks at a lower level of stimulus than high-threshold individuals. An extension of this model includes a simple form of learning. Within individual workers, performing a given task induces a decrease of the corresponding threshold, and not performing the task induces an increase of the threshold. This double reinforcement process leads to the emergence of specialized workers, that is, workers that are more responsive to stimuli associated with particular task requirements, from a group of initially identical individuals. The fixed response threshold model can be used to allocate tasks in a multiagent system, in a way that is similar to market-based models, where agents bid to get resources or perform tasks. The response threshold model with learning can be used to generate differentiation in task performance in a multiagent system composed of initially identical entities. Task allocation in this case is emergent and more robust with respect to perturbations of the system than when response thresholds are fixed. An example application to distributed mail retrieval is presented. In social insects, different activities are often performed simultaneously by specialized individuals. This phenomenon is called division of labor [253, 272]. Simultaneous task performance by specialized workers is believed to be more efficient than sequential task performance by unspecialized workers [188, 253]. Parallelism avoids task switching, which costs energy and time. Specialization allows greater efficiency of individuals in task performance because they “know” the task or are better equipped for it. All social insects exhibit reproductive division of labor: only a small fraction of the colony, often limited to a single individual, reproduces.

Efficient MapReduce secure data using Multiagent System

2018 ◽  
Vol 6 (5) ◽  
pp. 144-149
Author(s):  
H. Kousar ◽  
◽  
◽  
B.R.P. Babu
Keyword(s):  
Multiagent System ◽  
Secure Data

scholarly journals Using Machine Learning for Quantum Annealing Accuracy Prediction

Algorithms ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 187
Author(s):  
Aaron Barbosa ◽  
Elijah Pelofske ◽  
Georg Hahn ◽  
Hristo N. Djidjev
Keyword(s):  
Machine Learning ◽  
Maximum Clique ◽  
Classification Model ◽  
Maximum Clique Problem ◽  
Problem Instance ◽  
Np Hard ◽  
Machine Learning Classification ◽  
Hard Problems ◽  
Problem Instances ◽  
D Wave

Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a way to compute solutions of NP-hard problems that can be expressed in Ising or quadratic unconstrained binary optimization (QUBO) form. Although such solutions are typically of very high quality, problem instances are usually not solved to optimality due to imperfections of the current generations quantum annealers. In this contribution, we aim to understand some of the factors contributing to the hardness of a problem instance, and to use machine learning models to predict the accuracy of the D-Wave 2000Q annealer for solving specific problems. We focus on the maximum clique problem, a classic NP-hard problem with important applications in network analysis, bioinformatics, and computational chemistry. By training a machine learning classification model on basic problem characteristics such as the number of edges in the graph, or annealing parameters, such as the D-Wave’s chain strength, we are able to rank certain features in the order of their contribution to the solution hardness, and present a simple decision tree which allows to predict whether a problem will be solvable to optimality with the D-Wave 2000Q. We extend these results by training a machine learning regression model that predicts the clique size found by D-Wave.

Glutathione Ester But Not Glutathione Protects Against Cisplatin-Induced Ototoxicity in a Rat Model

2003 ◽  
Vol 14 (03) ◽  
pp. 124-133 ◽  
Author(s):  
Kathleen C.M. Campbell ◽  
Deb L. Larsen ◽  
Robert P. Meech ◽  
Leonard P. Rybak ◽  
Larry F. Hughes
Keyword(s):  
Auditory Brainstem Response ◽  
Outer Hair Cell ◽  
Tone Burst ◽  
Auditory Brainstem ◽  
Control Group ◽  
Brainstem Response ◽  
Group A ◽  
Direct Administration ◽  
Response Thresholds ◽  
Para Determinar

Glutathione (GSH) provides an important antioxidant and detoxification pathway. We tested to determine if direct administration of GSH or GSH ester could reduce cisplatin- (CDDP) induced ototoxicity. We tested eight groups of five rats each: a control group, a group receiving 16 mg/kg ip CDDP infused over 30 minutes, and six groups receiving either GSH or GSH ester at 500, 1000, or 1500 mg/kg intraperitoneally 30 minutes prior to 16 mg/kg CDDP. Auditory brainstem response thresholds were measured for click and tone-burst stimuli at baseline and 3 days later. Outer hair cell (OHC) loss was measured for the apical, middle and basal turns. The 500 mg/kg GSH ester reduced hearing loss and OHC loss, but protection decreased as dosage increased, suggesting possible toxicity. GSH was not significantly protective. The best GSH ester protection was less than we have previously reported with D-methionine. El glutatión (GSH) brinda una importante vía antioxidante y de cetoxificación. Realizamos una prueba para determinar si la administración directa de GSH o del éster de GSH podía reducir la ototoxicidad inducida por cisplatino (CDDP). Hicimos una evaluación en ocho grupos de cinco ratas cada uno: un grupo control, un grupo que recibió CDDP intraperitoneal a 16 mg/kg en una ínfusión durante 30 minutos y seis grupos que recibieron intraperitonealmente GSH o el éster de GSH a 500, 1000 o 1500 mg/kg, 30 minutos antes del CDDP a 16 mg/kg. Se midieron umbrales de respuestas auditivas del tallo cerebral tanto para clicks como para bursts tonales, al inicio y 3 días después. La pérdida de células ciliadas externas (OHC) fue establecida a nivel de las vueltas apical, media y basal. La dosis de 500 mg/kg de éster de GSH redujo la hipoacusia y la pérdida de OHC, pero la protección disminuyó conforme la dosis se incrementó, sugiriendo una posible toxicidad. EL GSH no resultó significativamente protector. El mejor efecto protector del éster de GSH fue menor que el previamente reportado con D-Metionina.

scholarly journals Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 126
Author(s):  
Hai-Feng Ling ◽  
Zheng-Lian Su ◽  
Xun-Lin Jiang ◽  
Yu-Jun Zheng
Keyword(s):  
Prevention And Control ◽  
Large Scale ◽  
Medical Services ◽  
The Novel ◽  
Multi Objective ◽  
Medical Supplies ◽  
Problem Instances ◽  
Novel Coronavirus ◽  
And Control ◽  
Minimum Ratio

In a large-scale epidemic, such as the novel coronavirus pneumonia (COVID-19), there is huge demand for a variety of medical supplies, such as medical masks, ventilators, and sickbeds. Resources from civilian medical services are often not sufficient for fully satisfying all of these demands. Resources from military medical services, which are normally reserved for military use, can be an effective supplement to these demands. In this paper, we formulate a problem of integrated civilian-military scheduling of medical supplies for epidemic prevention and control, the aim of which is to simultaneously maximize the overall satisfaction rate of the medical supplies and minimize the total scheduling cost, while keeping a minimum ratio of medical supplies reservation for military use. We propose a multi-objective water wave optimization (WWO) algorithm in order to efficiently solve this problem. Computational results on a set of problem instances constructed based on real COVID-19 data demonstrate the effectiveness of the proposed method.

scholarly journals The Inventory Routing Problem with Demand Moves

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Annelieke C. Baller ◽  
Said Dabia ◽  
Guy Desaulniers ◽  
Wout E. H. Dullaert
Keyword(s):  
Urban Areas ◽  
Research Literature ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Solution Approach ◽  
Holding Cost ◽  
Inventory Holding Cost ◽  
Problem Instances ◽  
Inventory Holding

AbstractIn the Inventory Routing Problem, customer demand is satisfied from inventory which is replenished with capacitated vehicles. The objective is to minimize total routing and inventory holding cost over a time horizon. If the customers are located relatively close to each other, one has the opportunity to satisfy the demand of a customer by inventory stored at another nearby customer. In the optimization of the customer replenishments, this option can be included to lower total costs. This is for example the case for ATMs in urban areas where an ATM-user that wants to withdraw money could be redirected to another ATM. To the best of our knowledge, the possibility of redirecting end-users is new to the operations research literature and has not been implemented, but is being considered, in the industry. We formulate the Inventory Routing Problem with Demand Moves in which demand of a customer can (partially) be satisfied by the inventory of a nearby customer at a service cost depending on the quantity and the distance. We propose a branch-price-and-cut solution approach which is evaluated on problem instances from the literature. Cost improvements over the classical IRP of up to 10% are observed with average savings around 3%.

scholarly journals A Multi-User Interactive Coral Reef Optimization Algorithm for Considering Expert Knowledge in the Unequal Area Facility Layout Problem

2021 ◽  
Vol 11 (15) ◽  
pp. 6676
Author(s):  
Lorenzo Salas-Morera ◽  
Laura García-Hernández ◽  
Carlos Carmona-Muñoz
Keyword(s):  
Coral Reef ◽  
Collaborative Design ◽  
Expert Knowledge ◽  
Fitness Function ◽  
Facility Layout ◽  
Layout Problem ◽  
New Strategy ◽  
Problem Instances ◽  
Expert Designer ◽  
First Time

The problem of Unequal Area Facility Layout Planning (UA-FLP) has been addressed by a large number of approaches considering a set of quantitative criteria. Moreover, more recently, the personal qualitative preferences of an expert designer or decision-maker (DM) have been taken into account too. This article deals with capturing more than a single DM’s personal preferences to obtain a common and collaborative design including the whole set of preferences from all the DMs to obtain more complex, complete, and realistic solutions. To the best of our knowledge, this is the first time that the preferences of more than one expert designer have been considered in the UA-FLP. The new strategy has been implemented on a Coral Reef Optimization (CRO) algorithm using two techniques to acquire the DMs’ evaluations. The first one demands the simultaneous presence of all the DMs, while the second one does not. Both techniques have been tested over three well-known problem instances taken from the literature and the results show that it is possible to obtain sufficient designs capturing all the DMs’ personal preferences and maintaining low values of the quantitative fitness function.

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