Abstract
In this chapter a new planning theory is developed. The rationale for needing this new theory lies in the fact that current spatial planning paradigms both seen from an academic as practice perspective, lack the possibility to deal with problems that are not straightforward, clearly defined and predictable: wicked problems. The majority of planning literature is still focusing on well-known problems and is operational within a governmental context. Despite the fact that a debate is emerging about the need for planning approaches that incorporate dynamic environments, look at the future from a change perspective and focus on the emergence of spatial order initiated by key actors outside government, recent publications show that 94% of the articles discuss traditional topics and approaches.
If planning needs to be prepared to incorporate wicked problems it is attractive to use complexity theory, which deals with complex adaptive systems. However, the majority of research in complexity theory in relation to planning and cities focuses on the understanding of emergence and self-organisation by developing ever more advanced computational models. This mathematicalisation of the city distracts the attention from intervening in these systems to improve preparedness in dealing with wicked problems.
The gap as shown above can be filled through the launch of a planning theory that deals with unpredictability of the future and incorporates complex systems behaviour. The theory is called Swarm Planning, because it emphasises swarm behaviour of the system to be beneficial for the overall resilience and lessen the impact of uncertainties, complexity and change.
Swarm Planning introduces two planning strategies: intervention in the system as a whole and free emergence through the attribution of individual components with Complex Adaptive System (CAS)-properties in order to perform self-organisation.
Keywords
6.1 Introduction
Climate change adaptation is seen as a wicked (VROM-raad 2007; Commonwealth of Australia 2007) or even a superwicked (Lazarus 2009) problem. A wicked problem is accurately defined in the seminal paper of Rittel and Webber: “Dilemmas in a General Theory of Planning” (Rittel and Webber 1973). Wicked problems are defined as being dynamic, they do not know a final solution, are “a one shot operation” and essentially unique. As planners, we do not have the right to be wrong.
Spatial planning is defined in many different ways. Dror for example (1973) describes planning as a process: “Planning is the process of preparing a set of decisions for action in the future, directed at achieving goals by preferable means”. In the course of this paper spatial planning is defined as the ‘co-ordination, making and mediation of space’ (Gunder and Hillier 2009: 4)
Current (and historic) discourses in spatial planning, such as incrementalism (referring to Lindblom 1959), post-positivism (as described in Allmendinger 2002a), communicative planning (amongst others: Habermas 1987, 1993; Healey 1997; Innes 2004), agonism (see: Mouffe 1993, 2005; Hillier 2003; Pløger 2004), reflexive planning (Beck et al. 2003; Lissandrello and Grin 2011) or even the actor network approach (Boelens 2010) do have considerable difficulties to deal with wicked problems, or solutions, or fail to take wicked problems as the subject of planning. Hence, the need for an alternative theory emerges. In this paper this theory, Swarm Planning, is explored and developed.
6.2 Problem Statement
Our world becomes increasingly complex and turbulent (see for instance Ramirez et al. 2008), as reflected in the fields of energy (peak oil and consequences of oil prices (Campbell and Laherrrère 1998; Campbell 1999, 2002a, b; Rifkin 2002; Belin 2008; Sergeev et al. 2009)), accelerated climate change (Tin 2008; Richardson et al. 2009; PBL et al. 2009; Sommerkorn and Hassol 2009), but also in the global economy. More specifically, climate adaptation, defined as a wicked problem itself, but also energy systems planning (Van Dam and Noorman 2005) are marginally connected with the spatial planning domain. This means that, inevitable, adaptation and energy planning take place in separate world, where they actually are not ‘planned’ as spatial systems. Meanwhile, regular planning (e.g. (urban) developments) continue to take place.
These problems are wicked and spatial planning lacks the processes, decision-making and tools to uptake them. Thus the problem can be stated as:
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Spatial planning is not used as a platform or framework for ‘solving’ these problems;
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Current spatial planning paradigms themselves predominantly focus on decision making within government for a well-described (planning) problem. Within planning theory there is a lack of methods and planning approaches for wicked problems.
While changes increasingly appear in a non-linear fashion, spatial planning increasingly lacks answers.
6.3 Approach
The research presented in this chapter distinguishes several pieces of work (Fig. 6.1).
In Sect. 6.4 a literature review about current planning paradigms has been conducted in two different ways. In the first place (Sect. 6.4.1) current paradigms as well as from the past have been identified and analysed on their usefulness for wicked problems. Secondly (Sect. 6.4.2), articles, published in 2010 and 2011 in four international planning journals (Planning Theory, Planning Theory and Practice, Australian Planner and European Planning Studies), were analysed on the merits of containing theories useful to complex problems. This illuminates the common typology of current subjects in planning journals.
In Sect. 6.5 complexity (Sect. 6.5.1) and planning for cities (Sect. 6.5.2) has been explored. On the one hand side because cities or areas are seen as complex adaptive systems (Portugali 2000; Batty 2005; Allen 1996; Dos Santos and Partidário 2011), but on the other hand the insights from complexity theory could be of use to develop a planning approach capable of dealing with wicked problems. The central question (Sect. 6.5.3) has been if current planning paradigms and/or in combination with scholarly writing on complexity and planning are sufficient of being able to make plans for wicked problems? The answer to this question led to the development of Swarm Planning Theory (Sect. 6.5.4). The theory of swarms (Fisher 2009; Miller 2010) and tipping points (Gladwell 2000), lessons from complexity (amongst others: Schwank 1965), existing examples of creating plans using the understanding of swarms (Oosterhuis 2006, 2011) and the use of complex adaptive systems properties (Roggema et al. 2012a) all were used to develop Swarm Planning theory, which enables planning to incorporate wicked problems. Finally (Sect. 6.6), the developed theory has been critically reflected upon and conclusions were drawn.
6.4 Current Planning Paradigms
In this section a brief overview of spatial planning paradigms is presented. Despite the fact that it is hardly possible to do justice to existing planning theories and paradigms in one paragraph each, it attempts to capture the main characteristics in order to come to a judgement-light of the applicability of each to deal with wicked problems. In-depth study and elaboration is required to provide a more thorough basis for the judgements. The current planning paradigm is analysed in two ways. In the first section a selection of well-known paradigms will be briefly described and their eventual shortcomings in the face of dealing with wicked problems will be examined. The second section will look into all articles published in four international planning journals over the years 2010 and 2011.
6.4.1 A Selection of Prevailing Planning Paradigms
In recent planning literature sparse, but strong signals can be found illuminating a change in planning paradigm. Scholars such as Newman, Boelens, Miraftab, Davy and Gunder all, from different angles, point at (the need for) planning ‘moving away’ from its traditional base: the government. Past planning paradigms, such as positivism, incrementalism, post-positivism, agonism and reflexive planning are all to a certain extent, but mostly inextricably connected to governmental agencies. These paradigms described briefly and their applicability to plan for wicked problems is considered.
The first discourse is positivism, which is build on the belief that data informs how to plan, and the logic of large amounts of data leads us to the one and only truth. Positivist planning schools look for general laws, are science based and top down organised (Allmendinger 2002b). For example, comprehensive rationality aims to understand the ‘whole’ through a thorough analysis of everything before problems can be defined and solved. And in systems theory cities are seen as systems, which can be modelled and changes can be predicted, once all characteristics are known (McLoughlin 1969). Positivist approaches require much data before conclusions can be drawn or plans can be made. For many organisations the collection and analyses, even with advanced computers, are hardly possible (Banfield 1973) and require large investments.
Especially when problems are complex, and most of the issues are nowadays (De Roo 2006), a rational comprehensive planning (positivist) approach is not possible and serious simplification of the problem is necessary (Lindblom 1959). Even though the increased computer capacity nowadays allows for dizzying calculations, it still is questionable whether the answers provided will deal with hardly predictable and surprising wicked problems. The question may be raised if, in order to deal with wicked problems, investments in deepening data collection and understanding the system are the most economic choice and, more in general, if a positivist approach will satisfy.
The second discourse, incrementalism, is extensively described in the seminal paper “the science of muddling through” (Lindblom 1959). Because it is not possible to comprehend all information, Lindblom elaborates on what he calls the method of Successive Limited.
Comparisons. It considers planning as a process of continually building out from the current situation, step-by-step and by small degrees. This incremental way is an adequate method for policy making if present policies are satisfactory, the nature of problems and the available means to deal with problems have a high degree of continuity (Dror 1964). However, incrementalism is an adversary process culminating in compromises of which the decisions tend to reflect the values of those in power, being a status quo. (Cates 1979).
When the environment presents itself as a non-incremental change, as many wicked problems do, this approach doesn’t work, because these changes are too large to respond to incrementally. In Lindbloms mindset: if the ‘limited comparison’ consists of two, of which one is a step change, the administrator would randomly choose the one implying limited change. Recent research illuminates climate change as a phenomenon characterised by ‘step changes’ (e.g. a significant change) (Jones 2010).
Under the umbrella of the post-positivist discourse (Allmendinger 2002a) several planning ‘schools’ share similar characteristics: a focus on subjective knowledge and endless possibilities for description (Allmendinger 2002b). Or, as Farmer wrote (1993: 392): post-structuralism could be characterised by its rejection of ‘master narratives’ and ‘foundational claims that purport to be based on science, objectivity, neutrality’ (cited in: Hillier and Cao 2011). Post-structuralism describes social and cultural systems (including cities) that are relational, open and dynamic, constantly in the process of emerging or ‘becoming’ different. Spaces and places are always in the process of being made and are unpredictable, especially in the longer term.
Examples of the, partially overlapping, post-positive planning ‘schools’ are collaborative planning (Healey 1997; Innes 2004; Innes and Booher 1999, 2004) or communicative rationality (Habermas 1987, 1993), post-modernism (Beauregard 1996; Jencks 1987; Allmendinger 2001) and communicative planning (Forester 1989).
In one of the central texts of this paradigm, Healey calls upon stakeholders to ‘…take a major leap in reflexive activity, to stand back from their particular concerns, to review their situation, to re-think problems and challenges, to work out opportunities and constraints, to think through courses of action which might be better than current practices and to commit themselves to changing things’ (Healey 2006: 244).
In general, post-positivism is oriented on structuring processes, stakeholder involvement and aiming for consensus.
Following Newman (2011): In assuming that communication and dialogue can operate in a neutral framework, collaborative planning theory imagines a level playing field where differences in power and wealth are somehow counteracted. Yet, we see how this formal neutrality and equality – where everyone is included as a ‘stakeholder’ – can function in an ideological way to legitimize an already assumed economic consensus, while de-legitimizing antagonism and dissent as irrational, violent and undemocratic.
In contrast with the consensus-oriented post-positivists, agonism, as Mouffe (1993, 1999, 2000, 2005), Hillier (2003) and Pløger (2004), amongst others are discussing, acknowledges and respects permanent conflicts in political communication. According to Mouffe, “the aim must be to transform an ‘antagonism’ into ‘agonism’ between ‘adversaries’ rather than ‘enemies’. In the political realm of agonism, compromises and consensus are possible, but ‘should be seen as temporary” (Mouffe 1999: 755). The task is to enhance ‘passion’ within politics and to realize that “agonistic confrontation is in fact [democracy’s] very condition of existence” (Mouffe 1999: 756). To see democracy as agonism means to go beyond the friend–enemy thinking, and seeing the participant one heavily disagrees with or does not understand, as an adversary ‘one can learn something from’ (Mouffe 2000). This does not require the negligence of interests and power-mechanisms, but the need to respect differences and disagreements radically. According to Pløger (2004) the art of ‘strife’ is essential, allowing for a respectful way of disagreement.
Following Newman again (2011): In this model, democratic agonism always takes place within the unacknowledged framework of the state, and it is unable to conceive of politics outside this framework. By situating democratic agonistic struggles primarily within the state and its parliamentary institutions, Mouffe leaves the actual political space of the state unchallenged.
As a reaction to changing societal circumstances, Ulrich Beck (1992, 1994) and others (Beck et al. 1994) have identified reflexive modernisation, a social theory, which emphasizes the new challenges current societies are experiencing due to the pressures exerted on existing institutions. A ‘second modernity’ emerges as the known rules of the first modernity are ‘in flux’ (Beck et al. 2003). Amin (2004) considers the capacity to change to be the basis. He acknowledges the fact that monitoring (and learning by monitoring) is a matter of developing a strategic and reflexive rationality (Lombardi 1994; Sabel 1994). Reflexive planning tries to capture this new modernity in planning. For example, De Roo and Porter (2007: 233) investigate the ways in which actors become continuously engaged in an “actor consulting model” for planning. Elsewhere, reflexive monitoring has been understood as “a participatory process of describing, evaluating, and reflecting on ongoing activities, designed to strengthen both the quality and impact of a project, concurrently, by feeding back into the project an understanding of its proceedings” (Grin and Weterings 2005: 5). Reflexivity has a strong temporal dimension it not only aims to solve present planning problems, but also imagines alternative trajectories for future action. It is seen as a new tool for generating critical knowledge and dialogue that can synthesise the perspectives of multiple actors in common understanding, within existing structural constraints and builds a collective imagination of alternative future possibilities. Reflexivity in planning focuses on ‘projectivity’, creativity and change; always bearing in mind that the future is uncertain, and that ready answers are not easy to come by (Lissandrello and Grin 2011).
Considerations: it acknowledges the changing times, but it bases itself in rationality and dominantly with the government in the lead. Therefore, the results depend largely on the actors involved and if not directed strongly has the risk of being ‘direction-loose’. Taking uncertainty as the interminable continuity a randomly chosen bunch of actors might reflex themselves into infinity. This approach has the risk in it of building a very accurate description of the changes in society and reflecting on this developments with a planning discourse of ‘continuously involving stakeholders’, which, in itself is valid, but leaves the question if these, even if carefully selected, stakeholders are capable of formulating responses to wicked problems.
However, reflexive modernity offers the framework of thought within which emerging debates take place within contemporary planning, concerning the fluidity of relations and interactions in planning processes, and the ways in which these processes influence future developments (e.g. Healey 2009; Hillier 2007). In this context Gunder (2011) calls for: “a critique that deconstructs both the planning discourses deployed, habitualised or otherwise derived, and their phantasmic affect upon both planners and the public. This is a call to challenge all positions which seek the security provided by the planner ‘who knows’. This is a call to challenge what is often, at best, a mono-rational practice of orthodox and repetitive universal.” In his pledge for post-anarchistic, or autonomous planning Newman emphasises the power of self-organising groups and organisations, planning for their own environments outside the governmental, political arena and creating herewith a disordered order of spaces that are ‘becoming’ (Newman 2011). In a debate provoking paper Boelens advocates planning to come from ‘outside inward’, led by actors out of the normal governmental planning arena (Boelens 2010). Miraftab describes the informal, insurgent, planning taking place in slums in South-Africa (Miraftab 2009) and Davy (2008) promotes unsafe planning on order to establish planning without tightening and dictating regulations. Gunder (2011) pledges to step away from the widespread code of what is unconsciously accepted ‘good planning’, positioning the planner as the one ‘who knows’, meanwhile, creating, following Davy: a “non-innovative state of mono-rationality”. An alternative, which is capable to include wicked problems, looms when the fundamental properties of western planning mono-rationality (Davy 2008) are left behind, being:
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‘Playing by the rules’, which in the case of wicked problems no longer rule;
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‘Repeat habitual prior experiences’, which in wicked problem country is useless, because every time the problem appears to be unique; and
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Creating a ‘non-innovative status quo’, which is contra-productive if the wicked problem is ‘already changing again’.
According to Davy, mono-rationality must be replaced by an ‘unsafe’ planning practice of poly-rationality, where liquid, turbulent or even wild boundaries of both planning thought and spatial territory can occur – literally, to do ‘it’ without the safety of a condom! This is a planning practice that takes risks, accommodates difference and encourages the new and creative. This type of practice is able to deal with uncertainties and the wicked character of problems such as climate change.
6.4.2 A Review of 2 Years of Planning Journals
The next step in the research is to examine whether unsafe, autonomous and poly-rational theories, concepts and strategies are discussed in the planning community, and if, in relation with the former, wicked problems are addressed. In order to gain insight about to what extent this specific part exists within the spatial planning debate, two volumes of four spatial planning journals have been analysed. The, in total 275 articles, which have been published in 2010–2011 in the Journals of Planning Theory (43), Planning Theory and Practice (34), The Australian Planner (45) and European Planning Studies (153), being the leading theoretical and practice oriented academic planning journals originating from two different continents, have been analysed. The articles were judged on criteria informing whether in the articles theories, concepts and strategies are discussed that potentially can deal with wicked problems. The following criteria have been distinguished:
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Integration (vs. thematic, specific, single subject): a wicked problem cannot be dealt with from a single narrow thematic perspective, because a singular solution for a problem that is wicked enables the problem to evolve into new forms the moment the thematic solution is executed. An integrated approach, in which themes and land-use functions are mutually connected and in which an area is approached as a whole, can deal much easier with unique, new and suddenly changing problems. Does the article approach problems in an integrative way or is it focusing on a specific theme or subject?
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Dynamic (vs. static): a division can be made in the aim of planning to stabilise the future or to emphasise dynamic environments, which need to be planned for and/or even need to be created. When wicked problems are taken into account spatial planning needs to recognise the existence of dynamic, continuous changing spatial settings and configurations. Does the article assume that planning tries to continue the current state or focuses it on dealing with changing environments or subjects?
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Intervention (vs. regulatory): planning can be orientated on arranging general and objective regulations that prohibit or allow certain land-use, or it may aim for a deliberate change. A planning intervention can be realised through design. In general, if problems are wicked they normally are not dealt with by putting regulations in place, as these problems are essentially unique. Does the article discuss a design approach or a planning intervention or does it focus on describing regulations and institutions?
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Paradigm shift (vs. status quo): when problems are new, especially if they are wicked, a new planning paradigm may emerge. The identification of these types of problems at an early stage illuminates their existence in the first place. If so, the early stages of a paradigm shift are announced, even if there are only small rudiments of it visible. In most of the cases however, planning in its current state, a status quo, is described, which is less suitable in dealing with changing circumstances and wicked problems. Does the article describe planning as it is currently and/or was in the past or does the article focuses on identifying a paradigm shift.
Having analysed the 275 articles, addressing the question if they contain integrated or thematic, dynamic or stable, interventionist or regulatory and shift or status quo issues, the results are striking and shocking at the same time (Fig. 6.2). The fundamental properties of western planning mono-rationality are still around. Even stronger, articles that address dynamic, integrated, intervention topics and paradigm shifts are hardly found.
The conclusion may be drawn that a very small portion of current planning discourse acknowledges fundamental changes in society, the changes in the environment and the need to plan for wicked problems. However, the current debate is predominantly in the process of raising awareness and describing what is going on. It addresses the necessity to replace old rules for new ones, which can respond to more complex issues and are based on networks, interrelations and connections. There are only a few scholars (e.g. Newman’s post-anarchism and Davy’s unsafe planning), who discuss the necessity to start planning in a more ‘non-linear’ way. In this article the search for a planning theory dealing with wicked problems draws upon these scholars and will search where wicked problems are closest related to: complexity theory.
6.5 Exploring Complexity
In order to plan for wicked problems, and more specifically for climate adaptation, we need to take into account that it is likely that climate change will force (step) changes (Jones 2010), that climate change has locality specific characteristics and it requires to bridge impacts occurring over a wide time-range. Therefore, it is useful to explore the potential of complexity theory in three ways. Firstly, we need to understand complex (adaptive) systems, their non-linearity and the idea that small changes might have big impacts, as well as the existence of bifurcation points and tipping points. Secondly, we need to understand cities self-organising systems. And thirdly, we need to build upon the former to make this knowledge available for planning.
6.5.1 Complexity Theory
Many scholars studied the complexity and self-organisation of non-linear dynamic (or adaptive) systems. Amongst these are the works of Prigogine and Stengers (1984), Gleick (1987), Lewin (1993), Mitchell Waldrop (1992), Cohen and Stewart (1994), Kauffman (1995), which are further elaborated and explained by authors such as Johnson (2001), Miller and Page (2007), Johnson (2007) and Northrop (2011). Key concepts from complexity theory, which are seen as useful in a planning context, are the self-organisation of complex systems, the surge for an actor to attractors, depicting a fitness landscape, the change and transformation of a complex system in times of crisis and the existence of bifurcation, ‘the point in time where for identical external conditions various possible structures can exist’ (Allen 1996) and tipping points, ‘the point at which the system ‘flips’ from one state to another’ (Gladwell 2000).
Adaptation of (or within) the system is an internal process of self-organisation, which is the tendency in complex systems to evolve toward order instead of disorder (Kauffman 1993). The state of equilibrium is called attractor. Complex adaptive systems self-organise and adapt in order to remain within their current attractor. The system only shifts to other attractors (alternative states) after a shock that drives the system out of its current state (e.g. due to significant (or ‘step’) changes in climate). Major adjustments are needed and after the shock the system will self-organise to achieve those.
The process this system goes through can be represented in the form of a fitness landscape (Fig. 6.3) (Mitchell Waldrop 1992; Langton et al. 1992). This fitness landscape includes favourable (the mountaintops) and less favourable (the valleys) positions. A complex system tends to move, while crossing less favourable valleys, to the highest possible position in the landscape, the attractor.
At the mountaintop, the adaptive capacity is highest, which allows the system to adapt more easily to changes in its environment. The pathway of the system is represented in Fig. 6.4. When a system self-organises it strives to reach a higher adaptive capacity by increasing order. When it reaches the mountaintop (B) it will continue to self-organise and increase order. However, by increasing order at this stage, adaptive capacity is decreasing, causing a less stable system (the state of fixed and unchangeable regulations and standards) and starts to move towards a new attractor. At this stage, the system is crossing the valley (from D to E) and searching for a new attractor, which can provide the system with renewed adaptive capacity. After reaching point E (a more chaotic state) two things can happen: the system dies (it didn’t reach/find the other attractor) or it self-organises in a new way and starts to build up a transformed system by increasing its order again until it reaches its highest adaptive capacity (the mountaintop) again (B). Point E is defined as the bifurcation point, or: the point where the system fundamentally separates the pathway towards a new equilibrium from the one ending its existence (‘die away’), also known as the tipping point, at which the system ‘flips’ from one state to another (Gladwell 2000).
These bifurcation, or tipping, points (1, 2) are the moments the system shifts from one state to another. In Fig. 6.5 these shifts are represented. At a certain point (1) the system in state x1 becomes less stable, for instance it is no longer capable of responding to the impacts of climate change. At this point the system (needs to) adapt quickly to the new environment and shifts into state x2, of higher complexity and order. If it fails to do so (the downward line) the system develops in a lower degree of complexity and cannot self-organise to deal with the new environment. It dies.
The behaviour of a complex system then consists of equilibrium phases and sudden changes (crises). In Fig. 6.6 (Timmermans et al. in print; after Prigogine and Stengers 1984) this process is visualised in the form of a slowly changing system A, which, due to external factors, such as climate change, can finally reach a less stable zone (2). Firstly, the system tries to maintain the equilibrium state A by suppressing change. At a certain moment, the system reaches a critical point (the bifurcation point) where it turns into instability (3). Here, at the edge of chaos, the system moves to a new equilibrium, A’ or B (4).
6.5.2 Cities as Complex Systems
These theoretical concepts have been applied to cities. However, the majority of scholars (Allen 1996; Batty 2005; Portugali 2000, 2006, 2008) use complexity theory mainly to understand self-organising processes in cities through modelling of reality. Modelling remains a central activity at the intersection of complexity and spatial science (O’Sullivan 2004) but there is a growing concern about the implicit limitations of this ‘orientation on modelling’ as the relevance of the links between spatial and complexity theories becomes much wider (O’Sullivan et al. 2006). Still, the main attention in recent academic writings focuses on different kinds of computational representations of spatial analyses (O’Sullivan et al. 2006) and the representation in models through agent-based modelling or cellular automata (Crawford et al. 2005). The question is whether this ‘mathematicalisation’ of the city offers more than only an understanding of self-organisation in cities, but merely supports cities in dealing with wicked problems, as it lacks the tools to influence the performance of the city. Spaces (and places) are, as described in Portugali (2006) mainly seen as an object to study, analyse, explain, understand, describe and model…. But this understanding is, to my knowledge, hardly used to inform planning and design processes on how to improve the quality of the city, or to better respond to and prepare for wicked problems.
6.5.3 Use of Complexity in Planning
As a bridge between the understanding of complexity in cities and planning for it, a key set of interrelated concepts that define a complex system (Manson 2001) can be helpful.
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At the core the relationships between its components and its environment, forming an ever-changing internal structure, determine the whole of the system. Due to the number and complexities of these relationships it is hardly possible to understand or predict the character of the whole system. Because of the wide array of complex internal relationships the system is in most cases able to respond to novel, external, relationships, but in the case there is no internal component capable of responding to novel external circumstances, which are for instance induced through climate change, this may end in a catastrophe for the system.
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The system exhibits emergence, e.g. the system wide characteristics stem from interactions amongst components (Lansing and Kremer 1993) and are thus much more than a simple addition of components qualities. It is difficult to anticipate change beyond the short term, because other components of the system adjust to the intervention in addition to other changes in the environment (Youssefmir and Huberman 1997). Any single change can have far-reading large-scale effects due to not understanding emergence from complexity (Lansing and Kremer 1993).
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A complex system performs change and evolution through three different capabilities: (1) self-organisation, e.g. the capability to adjust its internal structures to better interact with a changing environment; (2) Development of a dissipative structure, allowing the system to suddenly cross to a more organised state after being a certain period in a highly unorganised state (Schieve and Allen 1982); and (3) self-organised criticality, allowing the system to keep the balance between nearly collapsing and not doing so, caused by an internal restructuring, almost too rapid to accommodate, but necessary for survival (Scheinkman and Woodford 1994).
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Finally, path dependency defines the development of a system as ‘a trajectory as function of past states’ (O’Sullivan 2004). This may be true for most systems, Portugali demonstrated that in regards to planning the fact a plan has been released causes a reverse form of path dependency in the sense that the trajectory is a function of (not yet realised) future states (Portugali 2008). All of the former properties are found through the study of ecological and, to a lesser extent, economic systems.
The question, however, is whether we can use the knowledge derived from, mainly, ecosystems for artificial systems, such as cities. As demonstrated by Simon (1999, described in Portugali 2006) we can use the findings of natural science to apply in artificial systems, but only to a limited extent. As Portugali demonstrated (2000, 2008) social systems, such as cities and landscapes exhibit a dual complexity: the city as a whole is a complex adaptive system as is each of its parts (Portugali defines them as agents; e.g. human or organisational entities, Portugali 2008). This means that the whole can no longer be explained by the singular behaviour of individual components.
Learning from nature again, most systems performing swarm behaviour represent high resiliency, lessening the impact of uncertainties, complexity and change through the development of emerging patterns and structures (Van Ginneken 2009). Swarms (see Fisher 2009; Miller 2010) are self-organising systems in preparing and responding to changing circumstances, which is, according to Van Ginneken (2009), achieved through (1) the interactions taking place between a large number of similar and free moving ‘agents’, which (2) react autonomous and quick towards one another and their surrounding, resulting in (3) the development of a collective new entity and a coherent larger unity of higher order.
Swarm behaviour can be encouraged through increasing the adjustability of the building by programmatic labelling and tagging of building elements, enabling buildings to customise temporary desires or changing demands (Oosterhuis 2006, 2011),
The above forms the basis for developing the theory of Swarm Planning.
6.5.4 Proposition: Swarm Planning
The objective of this paper is to present the first contours and basic elements of Swarm Planning, which ultimately aims to increase the potential of a landscape or city to deal with wicked problems, such as climate change. Elaborating the above, this means that if the landscape could perform swarm behaviour, it increases its capacity to deal with uncertainty, complexity and change, hence dealing with wicked problems. Therefore, a planning theory that enables swarm behaviour to occur, supports landscapes to reach higher levels of adaptive capacity. This planning theory, Swarm Planning, needs to take at its core the dual complexity of the landscape and therefore to combine complex behaviour of the elements of the system and the complex adaptive behaviour of the system as a whole. And thus, Swarm Planning needs to actively intervene on both levels of the ‘dual complex’ landscape.
6.5.4.1 The Intervention
At the level of the whole, an intervention needs to take place in order to start the swarm to behave in the first place. In current theory, tipping points are identified after they have occurred (Gladwell 2000) or identify the patterns that announce these points (Scheffer 2009), but they are not planned. In essence, it describes the process of an evolving system, becoming unstable, ends up in a crisis, ‘tips’ and transforms through self-organisation to another stable state. However, in the case of climate change, this system change preferably anticipates the actual change. Hence, an early intervention must allow the system to be able to ‘flip’. We need to actively intervene in the system to start self-organising processes to anticipate the wicked problem. Hence, this requires an intervention point to get things started.
Obviously, the difficulty is to identify the location, the type and the actor to intervene. As demonstrated elsewhere (Roggema et al. 2012b) network theory holds the key to identifying the location. The type of intervention cannot be otherwise determined then through the local context (existing landscape combined with specific wicked problem). The actor identifies the point where and the type of intervention. The person or institution most eligible to decide upon this is the problem owner, not necessarily the government.
6.5.4.2 The Freedom to Emerge
The second level is the level of the parts (the elements in the landscape). At this level the components of the system need to make use of their joint capabilities to perform as a system as a whole. Only then, the system is able to produce swarm behaviour and achieve a higher adaptive capacity. Therefore, interacting relationships need to be provided with the qualities allowing them to develop emergent properties, to self-organise and to change (Manson 2001). The hypothesis is that if the landscape elements are attributed with the capabilities as described before, they will support swarm behaviour of the whole system. Once the individual components are attributed with these capabilities and free self-organisation will take place, the system will strive for the most optimal stable state (in general: the mountain top in the fitness landscape), which represents the highest adaptive capacity.
This theoretical proposition requires further research on the question how individual landscape elements can be attributed with qualities to allow them to perform emergent behaviour, self-organise and change. The first attempts to answer this question have been undertaken in the work of Kas Oosterhuis (2006, 2011), who attributed swarm characteristics to building elements, and by linking complex adaptive systems properties to landscape entities (Roggema 2011). However, further research is required in this area.
The proposition of Swarm Planning combines directive steering, in the form of an active design intervention (system level), with the freedom of individual landscape elements to shape (and self-organise) the system. The outcome of this process is fundamentally unpredictable, but this does not mean that we cannot be confident that the system, when performing swarm behaviour, reaches a higher adaptive capacity (or in complexity theory: reaches the top of the fitness landscape).
Part of a planning theory must be, in my opinion, besides a theoretical basis as presented above, a practical strategy and practical applications.
The theoretical basis has been used and translated into a practical approach (Roggema et al. 2012a) with the five layer strategy as the centrepiece, in which the first two layers identify the point of intervention, layer three arranges and defines the freedom to emerge and layers four and five allow for the individual components to self-organise.
The first practical applications of this theory have also been identified. In the work of Massoud Amin the principle of self-organisation in order to reach higher levels of agility in the energy network (Massoud Amin 2008a, b, 2009; Massoud Amin and Horowitz 2007) can be explained as an early form of Swarm Planning ‘avant la lettre’. A second body of knowledge has been developed, designing ‘swarm’ landscapes for regional climate adaptation (Roggema 2008a, b; Roggema and Van den Dobbelsteen 2008).
6.6 Conclusion
In this chapter it has been demonstrated that current planning discourses are strongly focused on the government as major actor and rely mainly on existing rules, regulations and established procedures. Moreover, the academic debate, as represented in four international planning journals illuminates the scarcity of articles focusing on strategies and practices, which focus on interventions, incorporate a changing and dynamic future and emphasise a paradigm shift. This illuminates a gap in planning practice and theory. This gap will lead to suboptimal preparation for climate change impacts, both in adaptation and in energy supply. This may be seen as very risk-full, because, even if decision-makers should decide that climate change impacts need to become part of planning practice immediately, it will take a shift in the planning frameworks, which in itself takes amounts of time. This time lag might imply that is becomes too late to implement the required changes on time.
Complexity theory might open the opportunity to integrate the characteristics of wicked problems in spatial planning and as demonstrated in this article has been subject of debate to link complexity and city and geography, but unfortunately complexity theory is mainly used in a mathematical, modelling way to better understand self-organising processes in cities and not to identify design interventions or plans to increase the capability of cities (and landscapes) to prepare for the impacts of wicked problems (e.g. climate change). This leads to suboptimal preparation of communities in those cities and landscapes.
Therefore, in this article a proposition is launched to develop a planning approach, which can integrate complexity theory and uses it for planning and design purposes. Named ‘Swarm Planning’ is an attempt to do so and, learning from the fact that cities have been attributed with a dual complexity (Portugali 2000), it identifies two major levels of intervention: the whole system, a level at which a strategic intervention is required, and the level of the individual components, to which the properties of complex adaptive systems need to be attributed in order to allow free emergence. Both levels in conjunction are able to perform swarm behaviour, which improves resiliency through lessening the impact of uncertainties, complexity and change.
Compared with the way planning is practiced in many institutions, thinking in points enforcing change and free emergence, is the opposite of current practice. Generally, tipping points are not sought, but comprehensive developments are seen as the interventions and these comprehensive interventions are planned in great detail and for entire areas, not allowing them to develop freely. The aversion against tipping points, and surprises, and the willing to paternalise the entire planning process, including its detailed execution, is grounded in the political culture in many countries where risk has to be avoided and uncertainties or ‘uncontrollabilities’ must be abandoned. However, pursuing the existing (and historical) path-dependent political pathways will lead to ‘more of the same’ policy, which, and this is for certain, will not produce the planning interventions that are required to deal with the wicked problem of climate change.
And it is true, the results of Swarm Planning are, partly, unpredictable and this is, especially to the responsible decision-makers a danger, but it is also a conditio sine qua non. Because in Swarm Planning the new state of the system is undefined, and not possible to define either, there always is the danger of ending up with the wrong outcome, but continuing on the same pathway of not adjusting will end in repetition of history and this will certainly not bring the answers to fundamental different problems of the future. Having said this, there is a lack of understanding of what the future system, planned through Swarm Planning, may be, and more research can be carried out in this field. However, given the unpredictability future state of complex adaptive systems it can be questioned whether more understanding will shine brighter lights on the actual future of the system.
This leaves alone the potential of Swarm Planning to be used in landscape (and city) design. As the example design demonstrates it is very well possible to design a landscape by making use of dynamic and complex principles. Moreover, it illuminates the potential for a community to slightly move towards an adapted and safe state and at the same time to pursue their own desires in realising a future safe and resilient living environment. As this is only the first, implicit, design, the approach deserves further testing and application.
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Roggema, R. (2012). Swarm Planning Theory. In: Roggema, R. (eds) Swarming Landscapes. Advances in Global Change Research, vol 48. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4378-6_6
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