CAST – City analysis simulation tool: an integrated model of land use, population, transport and economics

The paper reports on research into city modelling based on principles of Science of Complexity. It focuses on integration of major processes in cities, such as economics, land use, transport and population movement. This is achieved using an extended Cellular Automata model, which allows cells to form networks, and operate on individual financial budgets. There are 22 cell types with individual processes in them. The formation of networks is based on supply and demand mechanisms for products, skills, accommodation, and services. Demand for transport is obtained as an emergent property of the system resulting from the network connectivity and relevant economic mechanisms. Population movement is a consequence of mechanisms in the housing and skill markets. Income and expenditure of cells are self-regulated through market mechanisms and changing patterns of land use are a consequence of collective interaction of all mechanisms in the model, which are integrated through emergence

Learning game strategy design through iterated Prisoner's Dilemma

The article investigates games strategies on the basis of experiments with iterated Prisoner's Dilemma, a classical non-zero sum game. The objective is to determine which strategies have the best chance of winning. Although some strategies, like tit-for-tat, emerge as better than others in some cases, it appears that there is no overall winning strategy, but that success or failure of individual strategies depends upon the strategies adopted by a population of opponents. Therefore, the winning strategy will change dynamically, and will need to be determined while the game in progress. Based on the results of this work, a strategy engine for games development is proposed, and a future development of strategy middleware is discussed

Simulation of the complexity of cities with cast

This paper presents the experience of development and operation of CAST - a City Analysis Simulation Tool. The work is based on collaboration between researchers, urban practitioners and computer scientists. The underlying principles of CAST are designed to capture the complexity of cities through a component based approach driven by an extended Cellular Automata model structure. The system model obtained through the interaction of components addresses the key aspects of the complexity of cities by integrating economics, land use, transport and population dynamics. Operation of the model will be tested using data from several local authorities. CAST allows the rapid exploration of many 'what-if' scenarios including the impact of possible development and policy changes

Effects of neighbourhood structure on evolution of cooperation in N-player iterated prisoner's dilemma

In multi-agent systems, complex and dynamic interactions often emerge among individual agents. The ability of each agent to learn adaptively is therefore important for them to survive in such changing environment. In this paper, we consider the effects of neighbourhood structure on the evolution of cooperative behaviour in the N-Player Iterated Prisoner's Dilemma (NIPD). We simulate the NIPD as a bidding game on a two dimensional grid-world, where each agent has to bid against its neighbours based on a chosen game strategy. We conduct experiments with three different types of neighbourhood structures, namely the triangular neighbourhood structure, the rectangular neighbourhood structure and the random pairing structure. Our results show that cooperation does emerge under the triangular neighbourhood structure, but defection prevails under the rectangular neighbourhood structure as well as the random pairing structure

A scenario-based analysis of building energy performance

Inherent to the sustainability discourse is concern about the long-term future. If sustainable, cities must deliver positive benefits over their possibly long lifetime. Yet in formulating guidance and negotiating design choices for urban development, the consideration of uncertainty and potential future adverse conditions leading to failure is difficult to deal with. In this paper an approach to this issue that can inform the planning and/or urban design process is presented. It is based on a scenario analysis methodology (futures analysis), which herein is used to appraise the energy-efficiency strategies currently recommended in the UK planning system and best practice. The built environment is one of the major consumers of energy, and its energy efficiency is thereby central to any attempt to reduce carbon dioxide emissions. Through the analysis, some important factors that could undermine good energy performance emerge. Such findings can lead to the making of decisions that can enhance urban resilience. The first part of the paper provides an overview of the energy-efficient strategies examined, as well as current approaches for considering the evolution of present conditions when planning. The second part presents the futures analysis and its significance is demonstrated through a case study.

Testing energy efficiency in urban regeneration

One of the main objectives currently pursued in planning sustainable urban environments is the reduction of energy consumption. Strategies for energy and the built environment are given in UK planning policies. Yet the application of such strategies at a local scale requires careful contextual analysis, since local conditions may inhibit, or enhance, benefits that these strategies intend to deliver. More importantly, the permanence of such benefits over time can be disrupted if local conditions are undermined by unpredicted future events. This paper analyses the application of three energy conservation strategies recommended in planning guidance developed by Lancaster City Council for a flagship regeneration project. The strategies are energy-efficient building envelopes, the utilisation of passive solar design principles and the generation of renewable energy. Results from the analysis suggest that each one of these solutions could be vulnerable to unpredicted future events and that conditions to improve their resilience need to be built in today. The appraisal elicits interdependencies between solutions for energy efficiency and other sustainability solutions such as the quality of the public realm, the local microclimate, air quality and more. The discussion of these links leads to a series of recommendations designed to inform planning guidance.

Scenario archetypes:converging rather than diverging themes

Future scenarios provide challenging, plausible and relevant stories about how the future could unfold. Urban Futures (UF) research has identified a substantial set (>450) of seemingly disparate scenarios published over the period 1997–2011 and within this research, a sub-set of >160 scenarios has been identified (and categorized) based on their narratives according to the structure first proposed by the Global Scenario Group (GSG) in 1997; three world types (Business as Usual, Barbarization, and Great Transitions) and six scenarios, two for each world type (Policy Reform—PR, Market Forces—MF, Breakdown—B, Fortress World—FW, Eco-Communalism—EC and New Sustainability Paradigm—NSP). It is suggested that four of these scenario archetypes (MF, PR, NSP and FW) are sufficiently distinct to facilitate active stakeholder engagement in futures thinking. Moreover they are accompanied by a well-established, internally consistent set of narratives that provide a deeper understanding of the key fundamental drivers (e.g., STEEP—Social, Technological, Economic, Environmental and Political) that could bring about realistic world changes through a push or a pull effect. This is testament to the original concept of the GSG scenarios and their development and refinement over a 16 year period