scholarly journals Proposal of Sustainable Relief Goods Supply System for Large Scale Disaster -Autonomous Distributed System Based on the Response Threshold Model for Ant Colonies–

2019 ◽  
Vol 31 (1) ◽  
pp. 586-591
Author(s):  
Yusuke SATO ◽  
Satoshi IWATSU ◽  
Kazuyuki ITO
Keyword(s):  
Distributed System ◽  
Large Scale ◽  
Threshold Model ◽  
Supply System ◽  
Response Threshold ◽  
Ant Colonies ◽  
Response Threshold Model

Extended Contract Nets Application in Wood Drying Kiln

2012 ◽  
Vol 466-467 ◽  
pp. 449-453
Author(s):  
Xue Zhang ◽  
Ya Qiu Liu ◽  
Jun Peng Hua
Keyword(s):  
Large Scale ◽  
Ant Colony Algorithm ◽  
Threshold Model ◽  
Experimental Simulation ◽  
Response Threshold ◽  
Wood Drying ◽  
Consultation Process ◽  
Response Threshold Model ◽  
Improvement Method ◽  
Communication Traffic

The article aims at the problems such as the traditional contract nets model’s communication traffic is too heavy in the consultation process; task’s partition is fixed; evaluation index is not comprehensive, proposes a contract nets improvement method based on the bidding threshold and evaluation function by combining the response threshold model of the ant colony algorithm. This method introduce fuzzy synthetic computation, finding the potential cooperation relations between node agents, bottom-up decomposing the complex task, effectively reduce the negotiation time and communication flows, improve the efficiency of the system. The thesis combines wood drying application feature, and puts forward the improved model’s experimental simulation in wood drying kiln. The result shows that the improved method can effectively improve the performance of the Contract Net Protocol in large-scale multi-agent system. It provides technical basis for the realization of wood drying cluster control.

Response Threshold Model Based UAV Search Planning and Task Allocation

2013 ◽  
Vol 75 (3-4) ◽  
pp. 625-640 ◽  
Author(s):  
Min-Hyuk Kim ◽  
Hyeoncheol Baik ◽  
Seokcheon Lee
Keyword(s):  
Task Allocation ◽  
Threshold Model ◽  
Response Threshold ◽  
Model Based ◽  
Response Threshold Model ◽  
And Task

The emergence of division of labor in a structured response threshold model

2019 ◽  
Vol 517 ◽  
pp. 153-162 ◽  
Author(s):  
Viviane M. de Oliveira ◽  
Paulo R.A. Campos
Keyword(s):  
Division Of Labor ◽  
Threshold Model ◽  
Response Threshold ◽  
Response Threshold Model

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.

scholarly journals Task Assignment of the Improved Contract Net Protocol under a Multi-Agent System

Algorithms ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 70 ◽  
Author(s):  
Jiarui Zhang ◽  
Gang Wang ◽  
Yafei Song
Keyword(s):  
Task Allocation ◽  
Ant Colony Algorithm ◽  
Threshold Model ◽  
Response Threshold ◽  
Contract Net Protocol ◽  
Contract Net ◽  
Dynamic Contract ◽  
Response Threshold Model ◽  
Allocation Process ◽  
Run Time

Background: The existing contract net protocol has low overall efficiency during the bidding and release period, and a large amount of redundant information is generated during the negotiation process. Methods: On the basis of an ant colony algorithm, the dynamic response threshold model and the flow of pheromone model were established, then the complete task allocation process was designed. Three experimental settings were simulated under different conditions. Results: When the number of agents was 20 and the maximum load value was L max = 3 , the traffic and run-time of task allocation under the improved contract net protocol decreased. When the number of tasks and L max was fixed, the improved contract net protocol had advantages over the dynamic contract net and classical contract net protocols in terms of both traffic and run-time. Setting up the number of agents, tasks and L max to improve the task allocation under the contract net not only minimizes the number of errors, but also the task completion rate reaches 100%. Conclusions: The improved contract net protocol can reduce the traffic and run-time compared with classical contract net and dynamic contract net protocols. Furthermore, the algorithm can achieve better assignment results and can re-forward all erroneous tasks.

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