There are many studies dealing with the protection or restoration of wetlands and the sustainable economic growth of cities as separate subjects. This study investigates the conflict between the two in an area where city growth is threatening a protected wetland area. We develop a stochastic cellular automaton model for urban growth and apply it to the Vecht area surrounding the city of Hilversum in the Netherlands, using topographic maps covering the past 150 years. We investigate the dependence of the urban growth pattern on the values associated with the protected wetland and other types of landscape surrounding the city. The conflict between city growth and wetland protection is projected to occur before 2035, assuming full protection of the wetland. Our results also show that a milder protection policy, allowing some of the wetland to be sacrificed, could be beneficial for maintaining other valuable landscapes.

Some contemporary views of the universe assume information and computation to be key in understanding and explaining the basic structure underpinning physical reality. We introduce the Computable Universe exploring some of the basic arguments giving foundation to these visions. We will focus on the algorithmic and quantum aspects, and how these may fit and support the computable universe hypothesis.

Some contemporary views of the universe assume information and computation to be key in understanding and explaining the basic structure underpinning physical reality. We introduce the Computable Universe exploring some of the basic arguments giving foundation to these visions. We will focus on the algorithmic and quantum aspects, and how these may fit and support the computable universe hypothesis.

Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this paper we use information theory to provide abstract and concise measures of complexity, emergence, self-organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures. In a simplified version of the measures (focussing on the information produced by a system), emergence becomes the opposite of self-organization, while complexity represents their balance. We use computational experiments on random Boolean networks and elementary cellular automata to illustrate our measures at multiple scales.