Multiagent Systems: A Survey from a Machine Learning Perspective
Autonomous Robots
A Coevolutionary Approach to Learning Sequential Decision Rules
Proceedings of the 6th International Conference on Genetic Algorithms
Adding Continuous Components to L-Systems
L Systems, Most of the papers were presented at a conference in Aarhus, Denmark
A Taxonomy for artificial embryogeny
Artificial Life
An analysis of cooperative coevolutionary algorithms
An analysis of cooperative coevolutionary algorithms
Cooperative Multi-Agent Learning: The State of the Art
Autonomous Agents and Multi-Agent Systems
Compositional pattern producing networks: A novel abstraction of development
Genetic Programming and Evolvable Machines
A novel generative encoding for exploiting neural network sensor and output geometry
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Generating large-scale neural networks through discovering geometric regularities
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A comparison between cellular encoding and direct encoding for genetic neural networks
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
Competitive coevolution through evolutionary complexification
Journal of Artificial Intelligence Research
Improving coevolutionary search for optimal multiagent behaviors
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Generative and developmental systems
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
The sensitivity of HyperNEAT to different geometric representations of a problem
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
On the performance effects of unbiased module encapsulation
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Generative and developmental systems
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
HyperNEAT controlled robots learn how to drive on roads in simulated environment
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolving coordinated quadruped gaits with the HyperNEAT generative encoding
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Combining Multiple Inputs in HyperNEAT Mobile Agent Controller
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Evolving multi-modal behavior in NPCs
CIG'09 Proceedings of the 5th international conference on Computational Intelligence and Games
NEAT in HyperNEAT substituted with genetic programming
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Coevolution of heterogeneous multi-robot teams
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Transfer learning through indirect encoding
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolving heterochrony for cellular differentiation using vector field embryogeny
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Neuroevolution of mobile ad hoc networks
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Investigating whether hyperNEAT produces modular neural networks
Proceedings of the 12th annual conference on Genetic and evolutionary computation
A developmental approach to evolving scalable hierarchies for multi-agent swarms
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Generative and developmental systems
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Evolving policy geometry for scalable multiagent learning
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Evolving Static Representations for Task Transfer
The Journal of Machine Learning Research
HyperNEAT for locomotion control in modular robots
ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
Multi-agent role allocation: issues, approaches, and multiple perspectives
Autonomous Agents and Multi-Agent Systems
Evolving neural networks for geometric game-tree pruning
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Constraining connectivity to encourage modularity in HyperNEAT
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
HyperNEAT-GGP: a hyperNEAT-based atari general game player
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Generative and developmental systems
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Multirobot behavior synchronization through direct neural network communication
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
Command and control of teams of autonomous systems
Proceedings of the 17th Monterey conference on Large-Scale Complex IT Systems: development, operation and management
Generative and developmental systems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Hi-index | 0.00 |
This paper argues that multiagent learning is a potential "killer application" for generative and developmental systems (GDS) because key challenges in learning to coordinate a team of agents are naturally addressed through indirect encodings and information reuse. For example, a significant problem for multiagent learning is that policies learned separately for different agent roles may nevertheless need to share a basic skill set, forcing the learning algorithm to reinvent the wheel for each agent. GDS is a good match for this kind of problem because it specializes in ways to encode patterns of related yet varying motifs. In this paper, to establish the promise of this capability, the Hypercube-based NeuroEvolution of Augmenting Topologies (HyperNEAT) generative approach to evolving neurocontrollers learns a set of coordinated policies encoded by a single genome representing a team of predator agents that work together to capture prey. Experimental results show that it is not only possible, but beneficial to encode a heterogeneous team of agents with an indirect encoding. The main contribution is thus to open up a significant new application domain for GDS.