Evolution of Competing Strategies in a Threshold Model for Task Allocation

Author(s):  
Harry Goldingay ◽  
Jort van Mourik
Author(s):  
Tom De Wolf ◽  
Liesbeth Jaco ◽  
Tom Holvoet ◽  
Elke Steegmans

Author(s):  
Eric Bonabeau ◽  
Marco Dorigo ◽  
Guy Theraulaz

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.


Algorithms ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 70 ◽  
Author(s):  
Jiarui Zhang ◽  
Gang Wang ◽  
Yafei Song

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.


2020 ◽  
Vol 75 (3) ◽  
pp. 204-213
Author(s):  
Varvara A. Ryabkova ◽  
Leonid P. Churilov ◽  
Yehuda Shoenfeld

The pathogenesis of autoimmune diseases is very complex and multi-factorial. The concept of Mosaics of Autoimmunity was introduced to the scientific community 30 years ago by Y. Shoenfeld and D.A. Isenberg, and since then new tiles to the puzzle are continuously added. This concept specifies general pathological ideas about the multifactorial threshold model for polygenic inheritance with a threshold effect by the action of a number of external causal factors as applied to the field of autoimmunology. Among the external factors that can excessively stimulate the immune system, contributing to the development of autoimmune reactions, researchers are particularly interested in chemical substances, which are widely used in pharmacology and medicine. In this review we highlight the autoimmune dynamics i.e. a multistep pathogenesis of autoimmune diseases and the subsequent development of lymphoma in some cases. In this context several issues are addressed namely, genetic basis of autoimmunity; environmental immunostimulatory risk factors; gene/environmental interaction; pre-clinical autoimmunity with the presence of autoantibodies; and the mechanisms, underlying lymphomagenesis in autoimmune pathology. We believe that understanding the common model of the pathogenesis of autoimmune diseases is the first step to their successful management.


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