Topic
Dual-phase evolution
About: Dual-phase evolution is a research topic. Over the lifetime, 21 publications have been published within this topic receiving 168 citations.
Papers
1 Jan 2007
TL;DR: In this article, an alternative solution representation representation for the job shop scheduling problem in Ant Colony Optimisation is proposed, and a modified strategy for the constriction factor in Particle Swarm Optimization is proposed.
Abstract: Heuristics I.- Alternative Solution Representations for the Job Shop Scheduling Problem in Ant Colony Optimisation.- Analyzing the Role of "Smart" Start Points in Coarse Search-Greedy Search.- Concealed Contributors to Result Quality - The Search Process of Ant Colony System.- Ants Guide Future Pilots.- Complex Systems I.- Information Transfer by Particles in Cellular Automata.- An Artificial Development Model for Cell Pattern Generation.- Rounds Effect in Evolutionary Games.- Modelling Architectural Visual Experience Using Non-linear Dimensionality Reduction.- An Evolutionary Benefit from Misperception in Foraging Behaviour.- Simulated Evolution of Discourse with Coupled Recurrent Networks.- How Different Hierarchical Relationships Impact Evolution.- A Dual Phase Evolution Model of Adaptive Radiation in Landscapes.- Biological Systems I.- Directed Evolution of an Artificial Cell Lineage.- An Integrated QAP-Based Approach to Visualize Patterns of Gene Expression Similarity.- Complement-Based Self-Replicated, Self-Assembled Systems (CBSRSAS).- Self-maintained Movements of Droplets with Convection Flow.- Structural Circuits and Attractors in Kauffman Networks.- The Effects of Learning on the Roles of Chance, History and Adaptation in Evolving Neural Networks.- Unsupervised Acoustic Classification of Bird Species Using Hierarchical Self-organizing Maps.- The Prisoner's Dilemma with Image Scoring on Networks: How Does a Player's Strategy Depend on Its Place in the Social Network?.- Heuristics II.- Population-Based Ant Colony Optimisation for Multi-objective Function Optimisation.- Mechanisms for Evolutionary Reincarnation.- An Evolutionary Algorithm with Spatially Distributed Surrogates for Multiobjective Optimization.- Examining Dissimilarity Scaling in Ant Colony Approaches to Data Clustering.- Complex Systems II.- A Framework for the Co-evolution of Genes, Proteins and a Genetic Code Within an Artificial Chemistry Reaction Set.- In-Formation Flocking: An Approach to Data Visualization Using Multi-agent Formation Behavior.- A Principled Approach to Swarm-Based Wall-Building.- Pattern Extraction Improves Automata-Based Syntax Analysis in Songbirds.- Heuristics III.- A Modified Strategy for the Constriction Factor in Particle Swarm Optimization.- A Differential Evolution Variant of NSGA II for Real World Multiobjective Optimization.- Investigating a Hybrid Metaheuristic for Job Shop Rescheduling.- Enhancements to Extremal Optimisation for Generalised Assignment.- Biological Systems II.- Identification of Marker Genes Discriminating the Pathological Stages in Ovarian Carcinoma by Using Support Vector Machine and Systems Biology.- Ancestral DNA Sequence Reconstruction Using Recursive Genetic Algorithms.
31 citations
1 Jan 2006
TL;DR: Questions remain, especially about the ways in which different processes act in concert with one another, in particular, the relationships between self-organization, natural selection and the evolution of complexity remain unclear.
Abstract: A key challenge in complexity theory is to understand self-organization: how order emerges out of the interactions between elements within a system. [1980] pointed out that in dissipative systems (open systems that exchange energy with their environment), order can increase. Rather then being suppressed, positive feedback allows local irregularities to grow into global features. [1978] introduced the idea of an order parameter and pointed out that critical behaviour (e.g. the firing of a laser) always occurs at some predictable value of the parameter. Nevertheless, many questions remain, especially about the ways in which different processes act in concert with one another. In particular, the relationships between self-organization, natural selection and the evolution of complexity remain unclear.
25 citations
4 Dec 2007
TL;DR: Simulation results show that the DPE mechanism may indeed facilitate the appearance of complex diversity in a landscape ecosystem and argue that processes governing a wide range of self-organising phenomena are similar in nature.
Abstract: In this study, we describe an evolutionary mechanism - Dual Phase Evolution (DPE) - and argue that it plays a key role in the emergence of internal structure in complex adaptive systems (CAS) Our DPE theory proposes that CAS exhibit two well-defined phases - selection and variation - and that shifts from one phase to the other are triggered by external perturbations We discuss empirical data which demonstrates that DPE processes play a prominent role in species evolution within landscapes and argue that processes governing a wide range of self-organising phenomena are similar in nature In support, we present a simulation model of adaptive radiation in landscapes In the model, organisms normally exist within a connected landscape in which selection maintains them in a stable state Intermittent disturbances (such as fires, commentary impacts) flip the system into a disconnected phase, in which populations become fragmented, freeing up areas of empty space in which selection pressure lessens and genetic variation predominates The simulation results show that the DPE mechanism may indeed facilitate the appearance of complex diversity in a landscape ecosystem
16 citations
7 Dec 2008
TL;DR: It is shown that in evolving networks of agents, DPE can give rise to a wide variety of topologies, and can lead to the spontaneous emergence of stabilising modular structure.
Abstract: Dual Phase Evolution (DPE) is a widespread natural process in which complex systems adapt and self-organise by switching alternately between two phases: a phase of global interactions and a phase of local interactions We show that in evolving networks of agents, DPE can give rise to a wide variety of topologies In particular, it can lead to the spontaneous emergence of stabilising modular structure
13 citations
1 Jan 2017
TL;DR: It is shown that network properties underlie and define a whole family of nature-inspired algorithms, in particular, the network defined by neighbourhoods within landscapes (real or virtual) underlies the searches and phase transitions mediate between local and global search.
Abstract: Nature has inspired many algorithms for solving complex problems. Understanding how and why these natural models work leads not only to new insights about nature, but also to an understanding of deep relationships between familiar algorithms. Here, we show that network properties underlie and define a whole family of nature-inspired algorithms. In particular, the network defined by neighbourhoods within landscapes (real or virtual) underlies the searches and phase transitions mediate between local and global search. Three paradigms drawn from computer science—dual-phase evolution, evolutionary dynamics and generalized local search machines—provide theoretical foundations for understanding how nature-inspired algorithms function. Several algorithms provide useful examples, especially genetic algorithms, ant colony optimization and simulated annealing.
9 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2018 | 4 |
| 2017 | 1 |
| 2013 | 1 |
| 2012 | 1 |
| 2011 | 2 |
| 2010 | 1 |