There are two primary challenges faced by all complex, adaptive systems.
One is an uncertain and noisy environment.
The other is conflict.
Conflict arises when the interests of system components – whether genes, cells, individuals, or states – are not fully aligned.
Some have gone so far as to argue that lack of alignment, or “frustration,” in many body systems is the defining feature of complex systems.
In the long 3.5 billion year history of life on earth organisms and aggregates have devised manifold strategies in order to survive and prosper in the face of conflict.
The solutions that organisms have built for managing conflict are thought to have played a central role in facilitating the major transitions from simple aggregates to more integrated, social organisms, and cultures.
Although these transitions suggest nature has been successful at predicting and managing conflict, the problem is not a simple one.
Controlling conflict is tricky because it is both a destabilizing force and an agent of innovation – thus nature has evolved mechanisms of good management, not suppression.
Conflict can have multiple, nonlinear causes and effects, and these often lie at different timescales (e.g. evolutionary, ontogenetic, societal).
Conflict can be the outcome of competitive processes and involve deception or be generated by differing priorities, communications failures, and error.
Despite this complexity, data indicate that similar conflicts with comparable mechanisms of control have evolved at different levels of biological and social organization.
This suggests that there might be a universal class of mechanisms that have arisen across very different levels to control co-evolutionary escalation.
This focus area brings together evolutionary theorists, immunologists, experts on behavioral conflict in human and animal societies, computer scientists, molecular biologists, economists, and complex systems theorists all seeking to understand how conflict has shaped their systems.
Areas of research include principles of immunity in social, computer and biological immune systems; inductive game theory and the extraction of conflict strategies from time series data; the causes, consequences, and detection of anomalous patterns of conflict; the timescales of conflict and the implications of multiple timescales for individual and system prediction and control of conflict, robustness, and adaptation; tradeoffs between conflict as a source of innovation and conflict as a destabilizing perturbation; and computing adaptive conflict decision-making strategies under uncertainty.
Robustness may refer to:
- Robustness (evolution), the persistence of a system’s characteristic behavior under perturbations or conditions of uncertainty.
According to the kind of perturbation involved, it can be classified as mutational robustness, environmental robustness, etc
- Mutational robustness, the extent to which an organism's phenotype remains constant in spite of mutation
Robust decision, a decision that is as immune to uncertainty as is possible and looks good to all constituents long after it is made
Robust decision making
Robust statistics, a statistical technique that performs well even if its assumptions are somewhat violated by the true model from which the data were generated
Robustness (computer science)
- Fault-tolerant system and links thereof