Adaptive Task Allocation for Multi-agent Cooperation with Unknown Capabilities

2020 ◽  
Author(s):  
Jialun Li ◽  
Yushan Li ◽  
Yulai Weng ◽  
Jianping He
Keyword(s):  
Task Allocation ◽  
Multi Agent ◽  
Agent Cooperation

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

Market Clearing–based Dynamic Multi-agent Task Allocation

2020 ◽  
Vol 11 (1) ◽  
pp. 1-25
Author(s):  
Sofia Amador Nelke ◽  
Steven Okamoto ◽  
Roie Zivan
Keyword(s):  
Task Allocation ◽  
Market Clearing ◽  
Multi Agent

scholarly journals Improving Computational Efficiency in Crowded Task Allocation Games with Coupled Constraints

2019 ◽  
Vol 9 (10) ◽  
pp. 2117
Author(s):  
Ming Chong Lim ◽  
Han-Lim Choi
Keyword(s):  
Task Allocation ◽  
Random Sampling ◽  
Scheduling Algorithm ◽  
Stochastic Algorithm ◽  
Speed Of Convergence ◽  
Temporal Dependence ◽  
Real World Applications ◽  
Coupled Constraints ◽  
Multi Agent ◽  
Feasible Solutions

Multi-agent task allocation is a well-studied field with many proven algorithms. In real-world applications, many tasks have complicated coupled relationships that affect the feasibility of some algorithms. In this paper, we leverage on the properties of potential games and introduce a scheduling algorithm to provide feasible solutions in allocation scenarios with complicated spatial and temporal dependence. Additionally, we propose the use of random sampling in a Distributed Stochastic Algorithm to enhance speed of convergence. We demonstrate the feasibility of such an approach in a simulated disaster relief operation and show that feasibly good results can be obtained when the confirmation and sample size requirements are properly selected.

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).

scholarly journals A case study on availability of sensor data in agent cooperation

2010 ◽  
Vol 7 (3) ◽  
pp. 597-615
Author(s):  
Christian Johansson ◽  
Fredrik Wernstedt ◽  
Paul Davidsson
Keyword(s):  
Production Costs ◽  
Sensor Data ◽  
Energy Market ◽  
Physical Processes ◽  
Agent Based ◽  
Production And Distribution ◽  
Multi Agent ◽  
Problem Characteristic ◽  
Agent Cooperation

Multi-agent cooperation can in several cases be used in order to mitigate problems relating to task sharing within physical processes. In this paper we apply agent based solutions to a class of problems defined by their property of being predictable from a macroscopic perspective while being highly stochastic when viewed at a microscopic level. These characteristic properties can be found in several industrial processes and applications, e.g. within the energy market where the production and distribution of electricity follow this pattern. Another defining problem characteristic is that the supply is usually limited as well as consisting of several layers of differentiating production costs. We evaluate and compare the performance of the agent system in three different scenarios, and for each such scenario it is shown to what degree the optimization system is dependent on the level of availability of sensor data.

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