AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
Multiagent Bidding Mechanisms for Robot Qualitative Navigation
ATAL '00 Proceedings of the 7th International Workshop on Intelligent Agents VII. Agent Theories Architectures and Languages
Traderbots: a new paradigm for robust and efficient multirobot coordination in dynamic environments
Traderbots: a new paradigm for robust and efficient multirobot coordination in dynamic environments
On Recent Advances in Time/Utility Function Real-Time Scheduling and Resource Management
ISORC '05 Proceedings of the Eighth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing
A swarm based approximated algorithm to the extended generalized assignment problem (E-GAP)
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Dynamic Pricing Algorithms for Task Allocation in Multi-agent Swarms
Massively Multi-Agent Technology
Preferences of agents in decentralized task allocation
AI Communications
Multi-Robot Dynamic Task Allocation Using Modified Ant Colony System
AICI '09 Proceedings of the International Conference on Artificial Intelligence and Computational Intelligence
Engineering Applications of Artificial Intelligence
Decentralized Dynamic Task Allocation Using Overlapping Potential Games
The Computer Journal
Complex Task Allocation in Mobile Surveillance Systems
Journal of Intelligent and Robotic Systems
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
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In this paper, we propose a solution to the Multi-Robot Dynamic Task Allocation problem. We use Multi-Objective optimization in order to estimate, and subsequently, make an offer for its assignment. The motivation is to provide a generic solution, independent of the domain, with an aim to better utilize resources such as time or energy. The algorithm provides a significant degree of flexibility, and can be implemented in a number of diverse domains, provided the modeling of the parameters follows the convention presented. For this, we take into account - besides the distance traveled - the efficiency of a robot in a specific task type. The system has been shown to demonstrate scalability, as the experimental results indicate. It is also capable of responding to changes in the environment.