Quantifying evolutionary dynamics of swarm chemistry
نویسندگان
چکیده
This paper reports our recent efforts to quantitatively characterize the evolutionary dynamics of self-organizing patterns observed in Swarm Chemistry. Swarm Chemistry (Sayama 2009) is an artificial chemistry framework that can demonstrate self-organization of dynamic patterns of kinetically interacting heterogeneous particles. A swarm population in Swarm Chemistry consists of a number of simple self-propelled particles moving in a twodimensional continuous space. Each particle can perceive average positions and velocities of other particles within its local perception range, and change its velocity in discrete time steps according to kinetic rules similar to those of Reynolds’ Boids (Reynolds 1987). Each particle is assigned with its own kinetic parameter settings (similar to genotype) that specify preferred speed, local perception range, and strength of each kinetic rule. Particles that share the same set of kinetic parameter settings are considered of the same type. Several model extensions introduced in our recent work, including local information transmission among particles and their stochastic differentiation/re-differentiation, have made the model capable of showing morphogenesis and self-repair (Sayama 2010) and autonomous ecological/evolutionary behaviors of selforganized “super-organisms” made of a number of swarming particles (Sayama 2011; see Fig. 1).
منابع مشابه
Parallel evolutionary algorithm in high-dimensional optimization problem
An implementation of the combined evolutionary algorithm for searching extremum of functions with many parameters is proposed. The algorithm designed to optimize parameters of the molecular-dynamics reactive force field potential ReaxFF also can be efficient in many other extrema-searching problems with arbitrary complex objective function. The algorithm itself is a hybrid of two evolutionary m...
متن کاملStudy of Evolutionary and Swarm Intelligent Techniques for Soccer Robot Path Planning
Finding an optimal path for a robot in a soccer field involves different parameters such as the positions of the robot, positions of the obstacles, etc. Due to simplicity and smoothness of Ferguson Spline, it has been employed for path planning between arbitrary points on the field in many research teams. In order to optimize the parameters of Ferguson Spline some evolutionary or intelligent al...
متن کاملEvolutionary Dynamics of Ant Colony Optimization
Swarm intelligence has been successfully applied in various domains, e.g., path planning, resource allocation and data mining. Despite its wide use, a theoretical framework in which the behavior of swarm intelligence can be formally understood is still lacking. This article starts by formally deriving the evolutionary dynamics of ant colony optimization, an important swarm intelligence algorith...
متن کاملEvolutionary Population Dynamics and Multi-Objective Optimisation Problems
Problems for which many objective functions are to be simultaneously optimised are widely encountered in science and industry. These multiobjective problems have also been the subject of intensive investigation and development recently for metaheuristic search algorithms such as ant colony optimisation, particle swarm optimisation and extremal optimisation. In this chapter, a unifying framework...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2011