Ant Colony Optimization
Fluid Flow Approximation of PEPA models
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Bio-PEPA: An Extension of the Process Algebra PEPA for Biochemical Networks
Electronic Notes in Theoretical Computer Science (ENTCS)
Modelling Biological Compartments in Bio-PEPA
Electronic Notes in Theoretical Computer Science (ENTCS)
PRISM: probabilistic model checking for performance and reliability analysis
ACM SIGMETRICS Performance Evaluation Review
Bio-PEPA: A framework for the modelling and analysis of biological systems
Theoretical Computer Science
QEST '09 Proceedings of the 2009 Sixth International Conference on the Quantitative Evaluation of Systems
Dynamical Systems and Stochastic Programming: To Ordinary Differential Equations and Back
Transactions on Computational Systems Biology XI
PRISM 4.0: verification of probabilistic real-time systems
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
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Workers of the Argentine ant, Iridomyrmex humilis, are known to be capable to find efficiently the shortest route from their nest to a food source. Their approach is based on a simple pheromone trail-laying and following behaviour accessing only local information. In this note we explore the modelling and analysis of foraging ants in Bio-PEPA [8,6]. The simple case study concerns ants that need to cross a bridge with two branches of different length to reach food and carry the food home and is based on empirical data described by Goss and Deneubourg et al. [13,10]. We explore the conditions for which the shortest path emerges as the preferred one by the ants. The analysis is based on stochastic simulation and fluid flow analysis. The behaviour of ant colonies has inspired the development of an interesting class of optimisation algorithms ranging from alternative shortest path algorithms to new scheduling and routing algorithms, algorithms to solve set partition problems and for distributed information retrieval. Process algebraic fluid flow analysis may be an important additional technique to the analysis of such algorithms in a computationally efficient way.