Distributed Artificial Intelligence
Distributed Artificial Intelligence
Task differentiation in Polistes wasp colonies: a model for self-organizing groups of robots
Proceedings of the first international conference on simulation of adaptive behavior on From animals to animats
International Journal of Robotics Research
Designing emergent behaviors: from local interactions to collective intelligence
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
From Tom Thumb to the Dockers: some experiments with foraging robots
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
Learning to coordinate without sharing information
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Heterogeneous multi-robot cooperation
Heterogeneous multi-robot cooperation
On being a teammate: experiences acquired in the design of RoboCup teams
Proceedings of the third annual conference on Autonomous Agents
Computers and Intractability; A Guide to the Theory of NP-Completeness
Computers and Intractability; A Guide to the Theory of NP-Completeness
Evolving Beharioral Strategies in Predators and Prey
IJCAI '95 Proceedings of the Workshop on Adaption and Learning in Multi-Agent Systems
Adaptation and Learning in Multi-Agent Systems: Some Remarks and a Bibliography
IJCAI '95 Proceedings of the Workshop on Adaption and Learning in Multi-Agent Systems
Cooperative multi-robot box-pushing
IROS '95 Proceedings of the International Conference on Intelligent Robots and Systems-Volume 3 - Volume 3
Collective Robotic Site Preparation
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Multiagent Systems: A Survey from a Machine Learning Perspective
Autonomous Robots
Reactivity and Deliberation: A Survey on Multi-Robot Systems
Balancing Reactivity and Social Deliberation in Multi-Agent Systems, From RoboCup to Real-World Applications (selected papers from the ECAI 2000 Workshop and additional contributions)
Distributed Coordination in Heterogeneous Multi-Robot Systems
Autonomous Robots
A machine-learning approach to multi-robot coordination
Engineering Applications of Artificial Intelligence
A Novel Multi-robot Coordination Method Based on Reinforcement Learning
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues
Multi-agent robot systems as distributed autonomous systems
Advanced Engineering Informatics
Teamwork in self-organized robot colonies
IEEE Transactions on Evolutionary Computation
Towards cooperation of heterogeneous, autonomous robots: A case study of humanoid and wheeled robots
Robotics and Autonomous Systems
Task allocation for robots using inspiration from hormones
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
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Generating teams of robots that are able to perform their tasks over long periods of time requires the robots to be responsive to continual changes in robot team member capabilities and to changes in the state of the environment and mission. In this article, we describe the L-ALLIANCE architecture, which enables teams of heterogeneous robots to dynamically adapt their actions over time. This architecture, which is an extension of our earlier work on ALLIANCE, is a distributed, behavior-based architecture aimed for use in applications consisting of a collection of independent tasks. The key issue addressed in L-ALLIANCE is the determination of which tasks robots should select to perform during their mission, even when multiple robots with heterogeneous, continually changing capabilities are present on the team. In this approach, robots monitor the performance of their teammates performing common tasks, and evaluate their performance based upon the time of task completion. Robots then use this information throughout the lifetime of their mission to automatically update their control parameters. After describing the L-ALLIANCE architecture, we discuss the results of implementing this approach on a physical team of heterogeneous robots performing proof-of-concept box pushing experiments. The results illustrate the ability of L-ALLIANCE to enable lifelong adaptation of heterogeneous robot teams to continuing changes in the robot team member capabilities and in the environment.