Learning Legged Locomotion

Legged locomotion of biological systems can be viewed as a self-organizing process of highly complex system-environment interactions. Walking behavior is, for example, generated from the interactions between many mechanical components (e.g. physical interactions between feet and ground, skeletons an

IMG 305 - PEMBUNGKUSAN MAKANAN NOV.05.

We discuss the use of Agent-based Modelling for the development and testing of theories about emergent social phenomena in marketing and the social sciences in general. We address both theoretical aspects about the types of phenomena that are suitably addressed with this approach and practical guidelines to help plan and structure the development of a theory about the causes of such a phenomenon in conjunction with a matching ABM. We argue that research about complex social phenomena is still largely fundamental research and therefore an iterative and cyclical development process of both theory and model is to be expected. To better anticipate and manage this process, we provide theoretical and practical guidelines. These may help to identify and structure the domain of candidate explanations for a social phenomenon, and furthermore assist the process of model implementation and subsequent development. The main goal of this paper was to make research on complex social systems more accessible and help anticipate and structure the research process

Evolutionary self-organization in complex fluids

This paper explores the ability of molecular evolution to take control of collective physical phases, making the first decisive step from independent replicators towards cell-like collective structures. We develop a physical model of replicating combinatorial molecules in a ternary fluid of hydrocarbons, amphiphiles and water. Such systems are being studied experimentally in various laboratories to approach the synthesis of artificial cells, and are also relevant to the origin of cellular life. The model represents amphiphiles by spins on a lattice (with Ising coupling in the simplest case), coupled to replicating molecules that may diffuse on the lattice and react with each other. The presence of the replicating molecules locally modulates the phases of the complex fluid, and the physical replication process and/or mobility of the replicating molecules is influenced by the local amphiphilic configuration through an energetic coupling. Consequently, the replicators can potentially modify their environment to enhance their own replication. Through this coupling, the system can associate hereditary properties, and the potential for autonomous evolution, to self-assembling mesoscale structures in the complex fluid. This opens a route to analyse the evolution of artificial cells. The models are studied using Monte Carlo simulation, and demonstrate the evolution of phase control. We achieve a unified combinatorial framework for the description of isotropic families of spin-lattice models of complex phases, opening up the physical study of their evolution

From individuals to populations, approaches to the study of biological emergent phenomena

An assorted range of approaches have contributed to our understanding of the oscillatory behavior of population sizes in predation models. Among these are Mathematical Biology, Statistics and Artificial Life (ALife). In this paper, I will give a review of these different approaches. In addition, another approach, based on Evolutionary Game Theory, is proposed and discussed. This paper also suggests that a complementary study of both the Mathematical, Artificial Life and Game Theory approach is needed to explain some of the mysticism surrounding the global emergent behavior of local predator-prey relationships

Philosophical and scientific perspectives on emergence

SCOPUS: ar.jinfo:eu-repo/semantics/publishe