Multi Agent Based Dynamic Task Allocation

2014 ◽  
pp. 171-182 ◽  
Author(s):  
Arambam James Singh ◽  
Poulami Dalapati ◽  
Animesh Dutta
Keyword(s):  
Task Allocation ◽  
Agent Based ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Multi Agent

scholarly journals A multi-responsibility–oriented coalition formation framework for dynamic task allocation in mobile–distributed multi-agent systems

2018 ◽  
Vol 15 (6) ◽  
pp. 172988141881303 ◽  
Author(s):  
Bing Xie ◽  
Xueqiang Gu ◽  
Jing Chen ◽  
LinCheng Shen
Keyword(s):  
Coalition Formation ◽  
Task Allocation ◽  
Game Model ◽  
Multi Agent Systems ◽  
Coalition Game ◽  
Task Execution ◽  
Agent Systems ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Multi Agent

In this article, we study a problem of dynamic task allocation with multiple agent responsibilities in distributed multi-agent systems. Agents in the research have two responsibilities, communication and task execution. Movements in agent task execution bring changes to the system network structure, which will affect the communication. Thus, agents need to be autonomous on communication network reconstruction for good performance on task execution. First, we analyze the relationships between the two responsibilities of agents. Then, we design a multi-responsibility–oriented coalition formation framework for dynamic task allocation with two parts, namely, task execution and self-adaptation communication. For the former part, we integrate our formerly proposed algorithm in the framework for task execution coalition formation. For the latter part, we develop a constrained Bayesian overlapping coalition game model to formulate the communication network. A task-allocation efficiency–oriented communication coalition utility function is defined to optimize a coalition structure for the constrained Bayesian overlapping coalition game model. Considering the geographical location dependence between the two responsibilities, we define constrained agent strategies to map agent strategies to potential location choices. Based on the abovementioned design, we propose a distributed location pruning self-adaptive algorithm for the constrained Bayesian overlapping coalition formation. Finally, we test the performance of our framework, multi-responsibility–oriented coalition formation framework, with simulation experiments. Experimental results demonstrate that the multi-responsibility oriented coalition formation framework performs better than the other two distributed algorithms on task completion rate (by over 9.4% and over 65% on average, respectively).

Research on dynamic task allocation for multiple unmanned aerial vehicles

2017 ◽  
Vol 39 (4) ◽  
pp. 466-474 ◽  
Author(s):  
Yongfei Miao ◽  
Luo Zhong ◽  
Yufu Yin ◽  
Chengming Zou ◽  
Zhenjun Luo
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Task Allocation ◽  
Clonal Selection ◽  
Immune Memory ◽  
Allocation Model ◽  
Dynamic Task ◽  
Aerial Vehicles ◽  
Dynamic Task Allocation ◽  
Multi Agent ◽  
Multiple Unmanned Aerial Vehicles

To solve the distributed task allocation problems of search and rescue missions for multiple unmanned aerial vehicles (UAVs), this paper establishes a dynamic task allocation model under three conditions: 1) when new targets are detected, 2) when UAVs break down and 3) when unexpected threats suddenly occur. A distributed immune multi-agent algorithm (DIMAA) based on an immune multi-agent network framework is then proposed. The technologies employed by the proposed algorithm include a multi-agent system (MAS) with immune memory, neighbourhood clonal selection, neighbourhood suppression, neighbourhood crossover and self-learning operators. The DIMAA algorithm simplifies the decision-making process among agents. The simulation results show that this algorithm not only obtains the global optimum solution, but also reduces the communication load between agents.

Dynamic Task Allocation Based on Game Theory

2014 ◽  
Vol 926-930 ◽  
pp. 2790-2794
Author(s):  
Xiao Ping Wan ◽  
Shu Yu Li
Keyword(s):  
Game Theory ◽  
Task Allocation ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Agent System ◽  
Allocation Algorithm ◽  
Dynamic Task ◽  
Dynamic Task Allocation ◽  
Multi Agent ◽  
Lower Complexity

Multi-Agent System for task allocation problem, the introduction of game theory for dynamic task allocation modeling Multi-Agent Systems,Multi-Agent System proposed dynamic task allocation algorithm based on game theory.Experimental results show that the lower complexity of dynamic task allocation algorithm based on game theory in this article, the smaller amount of calculation,better robustness,task allocation scheme to obtain higher quality,with higher distribution

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