No abstract

No abstract

Springer Complexity is an interdisciplinary program publishing the best research and academic-level teaching on both fundamental and applied aspects of complex systems-cutting across all traditional disciplines of the natural and life sciences, engineering, economics, medicine, neuroscience, social and computer science.Complex Systems are systems that comprise many interacting parts with the ability to generate a new quality of macroscopic collective behavior the manifestations of which are the spontaneous formation of distinctive temporal, spatial or functional structures. Models of such systems can be successfully mapped onto quite diverse "real-life" situations like the climate, the coherent emission of light from lasers, chemical reaction-diffusion systems, biological cellular networks, the dynamics of stock markets and of the internet, earthquake statistics and prediction, freeway traffic, the human brain, or the formation of opinions in social systems, to name just some of the popular applications.Although their scope and methodologies overlap somewhat, one can distinguish the following main concepts and tools: self-organization, nonlinear dynamics, synergetics, turbulence, dynamical systems, catastrophes, instabilities, stochastic processes, chaos, graphs and networks, cellular automata, adaptive systems, genetic algorithms and computational intelligence.The three major book publication platforms of the Springer Complexity program are the monograph series "Understanding Complex Systems" focusing on the various applications of complexity, the "Springer Series in Synergetics", which is devoted to the quantitative theoretical and methodological foundations, and the "SpringerBriefs in Complexity" which are concise and topical working reports, case-studies, surveys, essays and lecture notes of relevance to the field. In addition to the books in these two core series, the program also incorporates individual titles ranging from textbooks to major reference works..

Games are as old as society, yet when a spatial designer enters the world of games, a new world opens-bright with novelty and possibility, a relatively unexplored instrument for shaping spaces that are more meaningful to humans. How much can an architect or an urbanist learn from games? Can games teach them about trust and ownership, as platforms with transparent rules valid for everyone, and with common goals? Can games teach them about learning and engagement, having fun with strangers while constantly being challenged individually and collectively? Can games teach them about training and strategizing for the real world, as they fail but are allowed the chance to restart? Can games teach them about communication and avoiding jargon, with their effective visual environment and simple language? From IBM's CityOne (2010) to Will Wright's SimCity (1989), and from Richard Duke's Metropolis (1969) to Buckminster Fuller's World Game (1961), a long list of games are predicated on cities in their staging, or these games take place directly in real urban areas. Some, as single-player games, run on predefined algorithms and quantitative feedback loops; others provide a multiplayer environment. Rules for the organization and composition of cities emerge from negotiations among multiple actors; an open system where new rules can be invented or unused rules abandoned, rather than a closed game with a predefined algorithm, are particularly promising for spatial designers. Perhaps better than a city-themed game, an environment that can be modified by the players could be useful in the pursuit of spatial designers learning from video games-environments that can host a wide range of players and do not focus on winning or losing, but rather, on building ex

Abstract. Fire disasters are common occurrences in the urban settlements of the Philippines. Concerned agencies like the Bureau of Fire Protection (BFP) and the Disaster and Risk Reduction Management Office (DRRMO) are constantly planning ways to prevent and mitigate fire disasters. The key to an effective plan against fire disaster is understanding how a potential fire can spread in a community. By combining both GIS and Probabilistic Cellular Automata (PCA), this paper solves the task of fire spread modeling and simulation. PCA is a model that consists of a regular grid of cells, whose cells are updated according to rules that take into account both the cell’s current state and the cell’s neighbors’ states. The model we developed factors in wind, building materials, and building density. The model was designed after several fires in major cities of Cebu, Philippines. An accuracy of 83.54% and a Cohen’s Kappa coefficient of 0.67 was achieved. Further, a web-based tool was developed to aid in fire disaster planning.