Para Limes

Complexity

Complexity

See the special lecture: Governance in Complexity, A Singaporean Perspective given by Mr Peter HO: Governance in Complexity at the Conference on Complex Systems 2019 (CCS2019)
Complexity lies at the heart of most real-world problems. Complexity evolves when a collection of objects (agents) competes for some kind of limited resource, like food, space, power, energy or wealth. Complexity results not from the number and heterogeneity of agents, but from the interactions between them.

complexity lens (using the word lens in a metaphorical way) is a tool for decision makers in industry, policymaking or elsewhere, to determine whether a problem is complex (in principle on any scale) and if so what level of complexity it has. Such a lens has many advantages, amongst others:

  • It will enable decisions makers to take a “Crude Look at the Whole”, before deciding whether to take action and if so what type of actions.
  • It will take the discussion about complex problems and how to deal with them out of the world of science and move it into the real world.
  • It will help decision makers to determine what type of resources must be mobilized to either solve the problem (if it is not complex) or develop effective interventions to steer the complex system in a direction that is beneficial for mankind.

To use such a lens, one needs the knowledge and expertise of all scientific disciplines and the conceptualizing power of philosophers. One also needs the creative imaginations of artists, and the hands-on experience of men and women of practice. Through their interactions they create the lens and bring the complexity into view.

The quintessence of Para Limes’ activities is to create and use complexity lenses by bringing together the strengths of different sciences, humanities, arts, engineering disciplines, tested knowledge, wisdom and youthful daring.

Typical architecture of a complex adaptive system


complex adaptive system can be seen as a collection of individual participants or agents (agents can be complex systems by themselves), each interacting with its neighbours. From these interactions new and often surprising phenomena emerge (upward arrows in figure). In turn, these phenomena define constraints that affect the interaction between the agents and its neighbors (down-going arrows), thus influencing the behavior and interaction of the agents in the system. Through these interactions the system continuously and dynamically adapts itself to its environment.

Complex adaptive systems have a number of characteristic features. Three are described below. Others are given in the textbox on this page.
  • Emergence manifests itself in a wide variety of phenomena such as climate change, spread of pathogens, cancer, urbanization, traffic jams, new structures of governance, financial crashes, loss of biodiversity, poverty, conflicts, youth unemployment, the impact of technologies on areas such as education, health, or communication, as well as the co-evolution of technologies with their users. A key characteristic of such phenomena is that they cannot be reduced to the individual components (agents) of the system: they are what makes the whole more than the sum of its parts.
  • Co-evolution. All systems exist within their own environment and are part of that environment. As their environment changes, they adapt to these changes. But because they are part of their environment, when they adapt, they change their environment, and as the environment changes, they need to adapt again, and so on. The system and its environment co-evolve.
  • Interconnectivity. It is through their connections that the agents can relate to one another. Through the interactions that take place along those connections the patterns (emerging properties) are formed and the feedback disseminated.
Generic Characteristics of Complex Systems
  • Self-organisation
  • Interdependence
  • Feedback
  • Far from equilibrium
  • Exploration of the space of possibilities
  • History and path dependence
  • Creation of new order
Generic Characteristics of Complex Systems
  • Self-organisation
  • Interdependence
  • Feedback
  • Far from equilibrium
  • Exploration of the space of possibilities
  • History and path dependence
  • Creation of new order
Complex problems are problems that involve one or more complex adaptive systems. Typically, there are no solutions to a complex problem. Interference with a complex adaptive system often leads to unexpected behavior of the system.

Complexity and complexity science refer to a way of looking at the world. Instead of looking at objects of study top-down in a reductionist manner as has been done for four centuries, complexity science seeks to look at its objects of study from the bottom up, seeing them as systems of interacting elements that form, change, and evolve over time. Complexity therefore is not so much a subject of research as a way of looking at systems. It is a “lens” through which to look at the world and what happens in it.