Publications
"Predicting the Unpredictable", Harvard Business Review, March 2002.
The collective behavior of people in crowds, markets, and organizations can easily elude any top-down analysis. Find out about ways to analyze--and even predict--the emergent phenomena resulting from group behavior.
"Don't Trust Your Gut", Harvard Business Review, May 2003.
How do you analyze more in less time? Powerful new decision-support tools can help executives quickly sort through vast numbers of alternatives and pick the best ones.
“Interactive Multi-Participant Tour Allocation”, Evolutionary Computation, 2004.
An evolutionary technique which allows human input to evaluate the fitness of a solution can be used to perform task allocation by integrating subjective criteria and subjective knowledge into the search process.
"Scale-Free Networks", Scientific American, May 2003.
Many networks—from the World Wide Web to a cell’s metabolic system to actors in Hollywood—are dominated by important nodes, or hubs, that have a seemingly unlimited number of links. These networks are remarkably resistant to accidental failures but extremely vulnerable to coordinated attacks.
"Agent-Based Modeling: Methods and Techniques for Simulating Human Systems", Proc. National Academy of Science, 2002.
The basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed.
"Dynamic Scheduling and Division of Labor in Social Insects", Adaptive Behavior, 2001.
A method for assigning tasks or resources, based on a model of division of labor in social insects, is applied to a scheduling problem and is able to adapt well to changing conditions.
"Swarm Intelligence: From Natural to Artificial Systems", Oxford University Press, 1999.
This book provides a rigorous look at the mechanisms underlying collective behavior in social insects and includes research from biology, neuroscience, artificial intelligence, robotics, operations research, and computer graphics.
"Swarm Intelligence: A Whole New Way to Think About Business", Harvard Business Review, 2001.
Research into the behavior of social insects has helped several companies, including Unilever, McGraw-Hill, and Capital One, to develop more efficient ways to schedule factory equipment, divide tasks among workers, organize people, and even plot strategy.
“How Word of Mouth Impacts Medicare Product Launch and Product Design”, Measuring Word of Mouth Vol. 3, Word of Mouth Research Symposium, 2007.
Read why WOM should be treated as an integral part of marketing strategy.
"The Effects of Word-of-Mouth: An Agent-Based Simulation of Interpersonal Influence in Social Networks", Word of Mouth Research Symposium, 2007.
Analyze the impact of the structure of a social network and the nature of individuals within that network on marketing and advertising.
"Decisions 2.0: The Power of Collective Intelligence", MIT Sloan Management Review, 2009.
Information markets, wikis and other applications that tap into the collective intelligence of groups have recently generated tremendous interest. But what”s the reality behind the hype?
"A More Rational Approach to New-Product Development", Harvard Business Review, 2008.
The Chorus model delivers new molecules at almost twice the speed and less than a third of the cost of the standard process.
"Inspiration for Optimization from Social Insect Behaviour", Nature, 2000.
Social insect behaviour has provided powerful methods for designing distributed control and optimization algorithms that exhibit a high degree of flexibility and robustness in a dynamic environment.
"Swarm Smarts", Scientific American, March 2000.
Using ants and other social insects as models, computer scientists have created software agents that cooperate to solve complex problems, such as the rerouting of traffic in a busy telecom network.
"When Intuition is Not Enough: Strategy in the Age of Volatility", Center for Business Innovation, January 2003.
Managers have long relied on intuition to make strategic decisions. Understand why today's times require a more adaptive approach to decision-making and preparing for an uncertain future.
"Making Interactive Evolutionary Graphic Design Practical", Computational Intelligence, 2008.
Explore the practical use of interactive evolution in 2D graphic design through a tool for evolving floor, wall and fabric tiles.
"Understanding and Managing Complexity and Risk", MIT Sloan Management Review, 2007.
Increased complexity of a company's systems - products, processes, technologies, organizational structures, legal contracts and so on - can create vulnerabilities. Three complimentary strategies can help mitigate the risk.
"Expecting the Unexpected: The Need for a Networked Terrorism and Disaster Response Strategy", Homeland Security Affairs, 2007.
A combination of two factors present the potential for a strategy that would not only facilitate flexible disaster and terrorism response, but could actually foster creative, ad hoc solutions to unforeseen situations that emerge during a crisis.
"The Perils of the Imitation Age", Harvard Business Review, 2004.
When information is plentiful, we often use it not to make better decisions based on the intrinsic characteristics of a situation but rather to imitate others—and their mistakes.
"A Drug Candidate Design Environment Using Evolutionary Computation", IEEE Transactions on Evolutionary Computation, 2008.
Our approach combines the capabilities of computational models with human knowledge using a Genetic Algorithm and Interactive Evolutionary Computation.
"Model Behavior: The Way a Company Really Works is Probably Not the Way Managers Think It Does", Optimize, 2002.
A fast-paced economy requires flexible, adaptive structures that self-organize internally in response to external changes.
"Co-Evolving Business Models: A Case Study with the Internet Service Provider (ISP) Industry", New Mathematics and Natural Computation, 2005.
Co-evolution is used to examine the long-term evolution of business models in the ISP industry.
listposts.php