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The Parable of the Hare and the Tortoise : How "Small Worlds" Reduce the Long Run Performance of Systems. David Lazer Program on Networked Governance Harvard University. Acknowledgements…. Allan Friedman NSF grant 0131923. Living in the (self-consciously) networked age.
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The Parable of the Hare and the Tortoise:How "Small Worlds" Reduce the Long Run Performance of Systems David Lazer Program on Networked Governance Harvard University
Acknowledgements… • Allan Friedman • NSF grant 0131923
Living in the (self-consciously) networked age • Growth of research on networks across disciplines • We live in an “smaller world” with ever-accelerating flows of information • Explosion of consultants, software, etc to make organizations “smaller”
The problem of parallel problem solving in human systems • Many agents working on same problem simultaneously • How is that problem solving aggregated?
Roadmap • The role of informational diversity in systemic performance • Networks as architecture for experimentation • Description of model • Results • Conclusion
Role of informational diversity • Sunstein, Nemeth, etc. • Informational diversity provides the menu of options in the system • However: pressures toward homogeneity, some of which may increase system performance (e.g., the elimination of bad solutions)
Processes of emulation • Neo-institutionalism– strong pressures for conformity (DiMaggio and Powell) • Networks play a key conduit for those pressures (Lazarsfeld, Friedkin, Lazer) • Convergence often not on system “optimum”, even when emulation is driven by success (Bikhchandani, Hirshleifer, and Welch; Strang and Macy)
Network structure • Cliquish • Small world– “six degrees of separation” (Milgram, Watts) • Birds of a feather (Lazarsfeld and Merton) • “Scale free” (Barabasi) • how does the architecture of the network affect balance between exploration and exploitation?
Small worlds (Milgram, Watts and Strogatts) Big world Small world
Network structure • Cliquish • Small world– “six degrees of separation” (Milgram, Watts) • Birds of a feather (Lazarsfeld and Merton) • “Scale free” (Barabasi) • how does the architecture of the network affect balance between exploration and exploitation?
Computational model • KISS principle– simplest possible model that captures some essence of reality • Agent-based– decision rules dictating agent behavior based on local conditions (not analytically tractable) • “Experimentally” manipulate parameters, test for robustness • Key question: what systemic patterns emerge?
Model • Problem space– what’s the problem agents are trying to solve? • Agent decision rules– how do agents seek improvements in performance? • Agent neighborhood– who do agents see (and emulate)?
Problem space • Key attribute of problem space is its ruggedness
Problem space • NK model (Kauffman) • N dimensions (19 in these simulations) • The marginal contribution of each dimension to performance is contingent on K other dimensions • K determines the ruggedness of the problem space (5 in most of these simulations) • Scores are calculated using a rank-preserving monotonic transformation
Decision rule • Capacity of agents to search problem space must be very limited
Decision rule • If someone agent can see is doing better than agent at time t, copy best alternative. • Otherwise, look at impact of randomly changing one dimension. If this is an improvement, move there. If not an improvement, stay at previous solution.
Informational velocity • Always looking at others? • If not: • Is communication synchronous (e.g., group meetings)? • Is communication asynchronous?
Network– determines neighborhood Linear (max degrees of separation = population size – 1) Fully connected (max degrees of separation = 1)
Basic model parameters • 100 agents • 200 time steps • 1000 simulations of each experiment • 20 NK spaces (N = 19, K = 5) • 50 randomly seeded starting points • Vary size, network structure, velocity, and synchronicity Code written in Java using the Repast libraries
Findings • Size • Network structure • Velocity • Synchronicity
The hare and the tortoise:Small worlds are good for a quick fix…
