Decentralized task allocation for heterogeneous agent systems with constraints on agent capacity and critical tasks

2012 ◽  
Author(s):  
Giulio Binetti ◽  
David Naso ◽  
Biagio Turchiano
Keyword(s):  
Task Allocation ◽  
Heterogeneous Agent ◽  
Agent Systems

Ant Colony Optimization for task allocation in Multi-Agent Systems

2013 ◽  
Vol 10 (3) ◽  
pp. 125-132 ◽  
Author(s):  
Lu Wang ◽  
Zhiliang Wang ◽  
Siquan Hu ◽  
Lei Liu
Keyword(s):  
Ant Colony Optimization ◽  
Task Allocation ◽  
Ant Colony ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
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).

Applying the Gale-Shapley Stable Matching Algorithm to Peer Human-Robot Task Allocation

2014 ◽  
Author(s):  
Elena L. Carano ◽  
Shih-Yuan Liu ◽  
J. Karl Hedrick
Keyword(s):  
Task Allocation ◽  
Evaluation Criteria ◽  
Stable Matching ◽  
Heterogeneous Agent ◽  
Single Item ◽  
Matching Algorithm ◽  
Task Distribution ◽  
Simulation Results ◽  
Task Features ◽  
Robot Task

When human and robotic agents work together, the challenge in assigning tasks lies in exploiting human strengths, such as expertise and intuition, while still managing the heterogeneous agent team in a near-optimal way. An extension to the Gale-Shapley stable matching algorithm that combines a sequential greedy approach is proposed to apply to task allocation missions. Conventional task features are modeled in the form of task preferences; agent inputs are modeled in the form of agent preferences. The algorithm is applied to a bomb defusal scenario, where bomb location is known but time for each agent to defuse each bomb is supplied through agent preferences. Simulation results are presented, and the sequential greedy Gale-Shapley algorithm is compared to a corresponding sequential single-item auction algorithm under three evaluation criteria — mission completion time, agent-task pair regret, and evenness of task distribution among agents.

Spatial snowdrift game in heterogeneous agent systems with co-evolutionary strategies and updating rules

2015 ◽  
Vol 24 (4) ◽  
pp. 040203 ◽  
Author(s):  
Hai-Jiang Xia ◽  
Ping-Ping Li ◽  
Jian-Hong Ke ◽  
Zhen-Quan Lin
Keyword(s):  
Evolutionary Strategies ◽  
Heterogeneous Agent ◽  
Agent Systems ◽  
Snowdrift Game
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