International Collaborative Research Program Causality in Complex Systems

1. International Collaborative Research Program Causality in Complex Systems Can we use “Attractors” as a way to reduce the dimensionality of the phase space of C&INs?

2. Rationale • How do experts make sense of complex phenomena in their domains? •  higher-level conceptual structures reduce dimensionality of searches • So what are the relevant higher-level concepts for C&INs? • We know interactions and dynamics are more important than composition and static configurations • The main sources of dynamically organised complexity are adaptive, self-organising and regulatory processes • Maybe these should be the building blocks of a higher-level conceptual map of the system? •  how do they interact? •  What are the recurring and/or persistent patterns and structures (attractors and repellors? What else?) that they can create? • Can we develop a “physics of interacting adaptive and S-O processes”?????

3. What is known about Interacting Adaptive (and S-O) Processes? • Population dynamics study co-evolution of species • Arms races and the Red Queen effect • Rehabilitation of group selection (DS Wilson, Okasha, and others) • Hot topic in theoretical biology: multi-level selection theories (-> one million hits in google) • Niche Construction – explicitly addressing interaction between genetic evolution and adaptive processes that shape the environment inherited by progeny  counterintuitive and very significant effects on outcomes (Odling-Smee, Laland, Feldman) • Interactions between different inheritance systems (Genetics, Epigenetics, Behavioural, Symbolic) (Jablonska and Lamb, ) • Our own conceptual framework for adaptation  Five levels of adaptation of which 4 involve applying adaptation to adaptive processes • Evo-devo studies address interaction between evolutionarily developed S-O processes and clade selection processes (Kirschner and Gerhart) • … lots more • But can we develop a general theory???

4. Some ways of thinking about it … • Bottom-Up: • Pick a real C&IN or a ‘toy’ version of one and try to explore its dynamics using these approaches • Top-down: • Start with generic model of adaptation • [variation, interaction, feedback, fitness-linked selection] operating on a system possessing [sense, ‘decide’, act] functions in a context • classify possible interaction pathways between two generic instances • Do this in a time-explicit way • Generalise to multiple interacting instances • What are the possible robust emergent patterns? • What are the possible transient phenomena that can significantly alter the dynamic development of the situation?

5. An attempt at the Bottom-up approach • Real Problem: How can we better understand the complex situation in the Afghanistan – Pakistan region and come up with more effective strategies for improving the situation? • Toy Problem: How can we better understand the intractability of the IED problem in a particular province and come up with more effective strategies for significantly reducing them?

6. Relevant CAS concepts Intractability • Multiscalarity • applies to: • agents • intents • attractors • timescales • decisions • actions Resilience Self-organisation How patterns of interaction  emergent patterns Robustness “attractors” ? • Adaptation • applies to: • ourselves (how we learn, develop strategy, plan and execute, improve capabilities, foster cooperation …) • adversaries (how they learn and change, how they decide what to do) • target populations (how they learn and change, how they decide what to do) • others …. thresholds tipping points transformability

7. Multiscale Intent Framework depends on understanding of context

8. feedback success-linked selection interaction variation Adaptation = “engines of change” in human systems • Through adaptation a complex adaptive system changes over time in a way which tends to increase its ‘success’ • Being adaptive requires: • Concept of ‘success or failure’, or ‘fitness’, for the system in its context • A source of variation in some internal details of the system, and • A fitness-linked selection process, i.e. the system preferentially retains/discards variations which enhance/decrease its fitness, which requires… • A way of evaluating impact of a variation on fitness – through feedback from interaction with its context (or from running an internal model). • Adaptation amounts to betting on the future being somewhat like the past. • Adaptation is a major process whereby complex adaptive systems such as living organisms, and organised groups change their characteristics and behaviours • We need to understand and harness it in many ways IOT influence the development of human systems • Detailed conceptual models and frameworks exist (refs available)

9. Hypotheses • Adaptive responses of agents can interact in synergistic or antagonistic ways • Synergistic networks of adaptive responses can create robust and persistent features - ‘attractors’ - of complex situations • An event or development that might perturb the ‘attractor’ stimulates adaptive responses from agents most directly affected, which then stimulate several waves of further adaptive responses from other agents through their interactions. • Net effect of all the adaptive responses is to return the situation to the ‘attractor’ region and stabilise it • Use of IEDs, corruption in public officials, cultivation of opium, are examples of such ‘attractors’ in the possibility space of PAKAF • Organised crime and drug use in big cities are other examples • Many ‘attractors’ at one scale interact to create larger scale ‘attractors’ eg IEDs, corruption, poppy cultivation and other robust features in PAKAF interact to create an intractable situation (one cant be solved without solving the others) • It is useful to develop understanding of the network of adaptive responses IOT identify potentially effective interventions • It is important to also understand the potential of the situation for being in different ‘attractors’ • to design intervention strategies to bring about more desirable ‘attractors’ at the relevant scales • AND to be aware of other potentially dangerous ‘attractors’ to be avoided. • Disciplined application of a methodology (yet-to-be-developed) based on these hypotheses would produce a strategy and accompanying framework of measures to be monitored that would give insight into where the situation is in its ‘attractor space’ and how it is tracking, providing the necessary feedback for adaptive implementation and refinement of the strategy

10. First steps to application to ‘toy’ scenario - motivating factors Ideologically driven • Who are the relevant agents? • - individuals & groups; • - specific & classes • What are their intent frameworks? • How do all the other agents respond to one changing their posture? • how do those responses trigger other responses and what is net effect? • how can we represent these networks of interacting adaptive responses ? Inspire, support, teach Better ways to pursue ideals Against principles Lead Work for Radical education Strategic effect IEDS individuals groups $$ recognition status Power struggles excitement anger intimidation Lead Work for Social pressure Nonradical education Better options to achieve power Coerce Reward Train Threaten Linked to others that benefit Better options to pursue goals pragmatically driven

11. First steps to application to ‘toy’ scenario - actions Engage in legitimate political and economic action Ideologically driven Inspire, support, teach Lead Work for Incite violence, publicise and praise violent acts, demonise opponents Seek to influence other groups & individuals away from violence IEDS individuals groups INCOMPLETE Coerce Reward Train Threaten Lead Work for pragmatically driven

12. Insights from relevant scientific domains • Examples of transformations of attractors: • Regime shifts in ecosystems • Interventions that change entrenched metacognitive behaviours • Stem cell research on switching cell fates • Phase changes in physical systems • Work on understanding resilience • Robust-Yet-Fragile systems • Cascading failures

13. What Next and Where to? • How to discover potential attractors that the situation is not currently in? • How to visualise? • What other structures might there be? • Regions of greater influencability (eg between two potential attractors?) • ???