----- Promise and Critique Gert de Roo.

Transcription

1 Understanding Planning and Complexity A Systems Approach Promise and Critique Gert de Roo g.de.roo@rug.nl

2 Planning Decision-making and Complexity Degree of Complexity of the and the characteristics of Physical Environment Systems (I to IV), with Class IV being Complex Systems

3 With regard to Planning and Decision-Making: What? From single, fixed and quantitative targets to multiple composite, dependent and qualitative objectives. Who? From central guiding to interactions among multiple stakeholders. How? From a technical rational approach to a communicative rationale approach. Single and fixed goal effectiveness Central guiding efficiency Participative interaction Multiple composite and line of decision

4 With regard to Complexity: Assumption 1: An open system evolves due to growing complexity in a movement from order to chaos a growing degree of complexity. Assumption 2: Complex systems emerge at the edge of order and chaos. Assumption 3: New, orderly systems emerge out of these complex systems, at a higher level. How do these assumptions relate to planning and decision-making?

5 Planning and Complexity The assumptions made, allow us: - To understand complexity and complex behaviour within Planning - To relate Planning to Fractals - And as such, to define progress and development within Planning

6 Planning and Complexity Technical rationality Communicative rationality Declining causality Entities become fuzzy Declining stability There is a degree of Complexity within Planning

7 Planning and Complexity Technical rationality Simple Straight forward Complex Very complex Chaotic Communicative rationality There is a degree of Complexity within Planning

8 Degree of Complexity: - Originates out of Assumption I - A consequence of Chaos Theory - Logically connects Systems I to III - As such it is a criteria for Planning and Decision-making

9 Four types of Systems: - Closed systems - Linear feet back systems - Systems randomly open to assimilation - Non linear adaptive systems (Wolfram, 2002)

10 Four classes of behaviour in cellular automata: - Class I yes or no, on or off, living or dead situations Steady equilibrium state - Class II developing static groups or patterns Oscillation between fixed states - Class III chaotic No predictable patterns or stability - Class IV Non linear adaptive systems Capable of producing extended transients (Kauffman, 1991) Class IV behaviour enables entities in the system to maximise the benefits of stability while retaining a capacity to change (Phelan, 1999)

11 Four meanings of comprehensiveness: - (Bounded) rationality Technical planning - Cases and contingent models Scenario planning - Telling stories Communicative planning - Wicked problems? (Verma, 1998)

12 Scenario Technical rationality Bulk of the issues? Communicative rationality 90 - > Simple Straight forward Complex Very complex Chaotic

13 Object oriented: focus on content and goals Technical rationality A B D C Communicative rationality Institutional or inter-subject oriented: focus on interaction and actors

14 Planning phases from a decision-making perspective: - Situation (Degree of complexity) - Position (What system, model or behaviour?) - Decision-making (From knowledge to actions) - Consequences (Effects with regard to estimated situation and position)

15 The logical steps of understanding situation position decision-making consequences, being arguments to planning, do count only for systems I, II and III. Understanding leads to arguments for choices of actions to be taken: - Class I systems: goal maximisation - Class II systems: goal optimisation, feet back and scenario s - Class III systems: process optimisation This does not work for Class IV systems!

16 With Class I to III systems we can formulate rules of behaviour, helping us to understand the consequences of our actions With Class IV systems the focus is to understand conditions under which systems behaves. Simulations are a means for this understanding. Complex Systems are a consequence of assumption II and theoretically explained by Complexity Theory

17 Systems I to III: - Causality, entity and stability in varying degrees - Objects and their interactions within a contextual environment - Identifying conditions of the system through the objects, interactions within the system and its environment - These conditions are qualifications for decision-making - There is a direct link between the conditions and the object of planning (physical environment) - Focus is on understanding the consequences of interfering - Planning transforming the system to our liking

18 Systems IV: - Connectivity, continuity and co-evolution - Path, transitions and dynamic behaviour bounded by attractors - Identifying conditions of the robustness and behaviour of the system through simple rules - These rules govern the interactions between lower-order elements that create emergent properties in the higher-level systems - The rules replace or represent reality, and do act as an intermediate in the process of planning and decision-making - Focus is on understanding the system s emergence - Planning anticipating to the systems behaviour?

19 Complex systems: - Large number of interactions - Interactions between low and high level systems - Simple rules underpinning complexity - Adaptation - Self-organisation - Co-evolution - Transforming, while retaining systems integrity - (Strange) attractors - Robust (within attractors) - Emergent properties - Fitness for purpose

20 Complex systems and Planning: - At the edge of order and chaos - In between systems II and III Technical rationality Communicative rationality - A different type of behaviour on the spectrum of rationality? -System Class IV?

21 Complex systems and Planning: - Or does assumption 2 mean a rise out of the spectrum representing assumption 1? Technical rationality Communicative rationality - And in that respect System Class IV is of a different kind? - Going towards a higher level, representing a new order (ass 3)?

22 Methods for understanding complex systems: - Cellular Automata - Autopoiesis - Non-linear dynamics - Multiscalar modelling -Gaming -Etc. These are known methods now used for understanding complex systems. What does this mean?

23 Issues in Planning to be considered Complex Systems: - Traffic and transport - Property rights - Urban development - Segregation - Interaction between physical, economic and social environment - Energy and spatial design -Etc

24 Promise: - A new and creative way of thinking about how the world around us works -Spectrum thinking connecting technical and communicative rationale in planning (degree of compl) - Bridging modernism and post-modernism - A better understanding of progress and development - Acceptance of emergence - Acceptance of autonomous processes in Planning - Acceptance control not to be the only paradigm in planning - An understanding of how planning will move forward: the new frontiers -Etc.

25 Critique: - Metaphor or reality? - Reality or rules and models representing reality? - Simulations and iterations only? - Degree of complexity or is it getting more complicated? - The aspect of complexity within methods as autopoiesis - Do Class IV Systems connect to Class I to III, and if so, how? - Are we asking the right questions, at all? - Planning decisions are often composed out of a pluriform setting, considering aspects of the various systems we acknowledge - Complex systems models fall short of explaining and operationalising processes in planning (urban change) - Modelling is not strongly developed in Planning, which leads to inadequate integration with complex systems thinking

26 Critique: - Real world applications are lagging behind the number of models developed - How valid is macro-behaviour obtained by aggregating microbehaviour (results out of model aggregation procedures)? - Complexity and complex systems remain assumptions essentially, not supported yet with real world hard data - While complex system modelling employs systems based on absolute and relative space, measures of relational space are being ignored - Model outputs cannot differentiate causal and accidental events, and as such these cannot support the teleological explanations that planning and decision-making demand - What about emergence of order?

27 While arguments are building up in support of Class IV systems, it is still a giant step away from practical and effective use in Planning and Decision-making

28 Therefore: A Book Proposal That is both positive and critical: Ashgate Publishers is appreciating our initiative and will start publishing The Aesop series in Complexity and Planning

29 Thank you