Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Cooperative Mobile Robotics: Antecedents and Directions
Autonomous Robots
The Legion System: A Novel Approach to Evolving Hetrogeneity for Collective Problem Solving
Proceedings of the European Conference on Genetic Programming
Behavioral diversity in learning robot teams
Behavioral diversity in learning robot teams
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
An overview of evolutionary algorithms for parameter optimization
Evolutionary Computation
Distributed, Physics-Based Control of Swarms of Vehicles
Autonomous Robots
Evolving cooperative strategies for UAV teams
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
Evolving an ecology of two-tiered organizations
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
The Cooperative Coevolutionary (1+1) EA
Evolutionary Computation
Robustness in cooperative coevolution
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Neuro-evolution for a gathering and collective construction task
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Genetic team composition and level of selection in the evolution of cooperation
IEEE Transactions on Evolutionary Computation
Sequential auctions for heterogeneous task allocation in multiagent routing domains
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Behavior-based motion planning for group control
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Theoretical convergence guarantees for cooperative coevolutionary algorithms
Evolutionary Computation
Scalable and robust shepherding via deformable shapes
MIG'10 Proceedings of the Third international conference on Motion in games
A multi-agent organizational framework for coevolutionary optimization
Transactions on Petri nets and other models of concurrency IV
An algorithm for distributed on-line, on-board evolutionary robotics
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Designing Effective Heterogeneous Teams for Multiagent Routing Domains
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
An overview of cooperative and competitive multiagent learning
LAMAS'05 Proceedings of the First international conference on Learning and Adaption in Multi-Agent Systems
Evolving team behaviors with specialization
Genetic Programming and Evolvable Machines
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Many mobile robot tasks can be most efficiently solved when a group of robots is utilized. The type of organization, and the level of coordination and communication within a team of robots affects the type of tasks that can be solved. This paper examines the tradeoff of homogeneity versus heterogeneity in the control systems by allowing a team of robots to coevolve their high-level controllers given different levels of difficulty of the task. Our hypothesis is that simply increasing the difficulty of a task is not enough to induce a team of robots to create specialists. The key factor is not difficulty per se, but the number of skill sets necessary to successfully solve the task. As the number of skills needed increases, the more beneficial and necessary heterogeneity becomes. We demonstrate this in the task domain of herding, where one or more robots must herd another robot into a confined space.