19 research outputs found
EvoMachina : a novel evolutionary algorithm inspired by bacterial genome reorganisation
EvoMachina is a novel natural computation algorithm, inspired by recent understandings of the processes of genome reorganisation in bacteria and viruses. It has been developed as part of the EU FP7 project EvoEvo, taking inspiration from its biological experiments, and developed to support Living Technology applications. This abstract outlines the conceptual model underlying EvoMachina, its implementation, and a reference application
A Transactional Architecture for Simulation
Abstract-We are developing a concurrent, agent-based approach to complex systems simulation as part of the CoSMoS project. In such simulations an agent's behaviour can typically be characterised as a series of queries and updates to its environment-a "transactional" pattern of interaction familiar to programmers of database systems. We explore how ideas from the field of databases, such as optimistic approaches to consistency and replication, may profitably be applied to the field of simulation, and how the constraints of modern databases can be relaxed to yield better performance while maintaining simulation validity
Environment Orientation : a structured simulation approach for agent-based complex systems
Complex systems are collections of independent agents interacting with each other and with their environment to produce emergent behaviour. Agent-based computer simulation is one of the main ways of studying complex systems. A naive approach to such simulation can fare poorly, due to large communication overhead, and due to the scope for deadlock between the interacting agents sharing a computational platform. Agent interaction can instead be considered entirely from the point of view of the environment(s) within which the agents interact. Structuring a simulation using such Environment Orientation leads to a simulation that reduces communication overhead, that is effectively deadlock-free, and yet still behaves in the manner required. Additionally the Environment Orientation architecture eases the development of more sophisticated large-scale simulations, with multiple kinds of complex agents, situated in and interacting with multiple kinds of environments. We describe the Environment Orientation simulation architecture. We report on a number of experiments that demonstrate the effectiveness of the Environment Orientation approach: a simple flocking system, a flocking system with multiple sensory environments, and a flocking system in an external environment
Environment Oriented Simulation
Complex systems are collections of independent agents interacting to as to produce emergent, often unexpected, behaviour. Computer based simulation is one of the main ways of studying complex systems and a naıve approach to such simulation is fraught with difficulty due to the scope for deadlock in various patterns of interaction between the agents which are of necessity sharing aspects of the computational platform.
Agent behaviour, though, can be entirely looked at from the point of view of the environments within which the agents interact. Structuring a simulation purely in this manner leads to a simulation that has essentially no tendency to deadlock and still behaves in the manner required.
A number of experiments are conducted to demonstrate the feasibility of this approach. These start with a simple flocking system and continue through an investigation of the ways in which multiple environments can best be combined. Finally, a larger scale experiment investigating the evolution of variety in a rich environment shows that interesting results can be obtained of a simulation constructed in this manner
A Transactional Architecture for Simulation
We are developing a concurrent, agent-based approach to complex systems simulation as part of the CoSMoS project. In such simulations an agent's behaviour can typically be characterised as a series of queries and updates to its environment--a ''transactional'' pattern of interaction familiar to programmers of database systems. We explore how ideas from the field of databases, such as optimistic approaches to consistency and replication, may profitably be applied to the field of simulation, and how the constraints of modern databases can be relaxed to yield better performance while maintaining simulation validity
Complex systems models: engineering simulations
As part of research towards the CoSMoS unified infrastructure for modelling and simulating complex systems, we review uses of definitional and descriptive models in natural science and computing, and existing integrated platforms. From these, we identify requirements for engineering models of complex systems, and consider how some of the requirements could be met, using state-of-the-art model management and a mobile, process-oriented computing paradigm