Machine Learning - Special issue on inductive transfer
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
The Simple Genetic Algorithm: Foundations and Theory
The Simple Genetic Algorithm: Foundations and Theory
The Emergence of Cellular Computing
Computer
Complex information processing: a file structure for the complex, the changing and the indeterminate
ACM '65 Proceedings of the 1965 20th national conference
Environment-Independent Reinforcement Acceleration
Environment-Independent Reinforcement Acceleration
A model of inductive bias learning
Journal of Artificial Intelligence Research
An architecture for self-organising evolvable virtual machines
Engineering Self-Organising Systems
Self-adaptation and dynamic environment experiments with evolvable virtual machines
ESOA'05 Proceedings of the Third international conference on Engineering Self-Organising Systems
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Inspired by advances in evolutionary biology we extended existing evolutionary computation techniques and developed a self-organising, self-adaptable cellular system for multitask learning, called Evolvable Virtual Machine (EVM). The system comprises a specialised program architecture for referencing and addressing computational units (programs) and an infrastructure for executing those computational units within a global networked computing environment, such as Internet. Each program can be considered to be an agent and is capable of calling (co-operating with) other programs. In this system, complex relationships between agents may self-assemble in a symbiotic-like fashion. In this article we present an extension of previous work on the single threaded, single machine EVM architecture for use in global distributed environments. This paper presents a description of the extended Evolvable Virtual Machine (EVM) computational model, that can work in a global networked environment and provides the architecture for asynchronous massively parallel processing. The new computational environment is presented and followed with a discussion of experimental results.