 Evolving Logic's Robust Adaptive Planning™ (RAP™) had its genesis in ten years of scholarly and policy work, primarily at RAND. Here is a collection of essays and journal articles which describe the theoretical basis of RAP™ and the CAR™ (Computer Assisted Reasoning®) technology that power our revolutionary new tools.
Computer Assisted Reasoning®
CAR™, based on exploratory modeling methods in the scholarly literature, is an approach to human-computer interaction that supports decision-making under conditions of deep uncertainty.
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Bankes, Steven C. Robert J. Lempert, and Steven W. Popper, "Computer-Assisted Reasoning," Computing in Science and Engineering, 2001, pp. 71-77.
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"Exploratory Modeling," Steven C. Bankes, Operations Research Encyclopedia, 1999
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"Exploratory Modeling: Search Through Spaces of Computational Experiments," Steven C. Bankes and James Gillogly, Proceedings of the Third Annual Conference on Evolutionary Programming, 1994.
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"Validation of Exploratory Modeling," Steven C. Bankes and James Gillogly, The Society for Computer Simulation, 1994.
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"Parametric Modeling of the Temporal Dynamics of Neuronal Responses Using Connectionist Architectures," Steven C. Bankes and Daniel P. Margoliash, Journal of Neurophysiology, 1993.
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"Exploratory Modeling for Policy Analysis," Steven C. Bankes, Operations Research, 1993.
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"Computer Assisted Reasoning for Decision Support," Steven C. Bankes.
Robust Adaptive Planning™
When faced with deep uncertainty, managers often respond with flexibility and by being adaptive. RAP™ software can help decision-makers systematically find adaptive-decision strategies robust across a wide range of uncertainty. These papers describe how, focusing on the public policy problem of global climate change.
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Robert J. Lempert, Nebojsa Nakicenovic, Daniel Sarewitz, Michael Schlesinger, 2004: "Characterizing Climate-Change Uncertainties for Decision-makers," Climatic Change, 65, 1-9.
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Lempert, Robert J., Steven W. Popper and Steven C. Bankes, Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis, Santa Monica, Calif., RAND MR-1626, 2003.
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Lempert, Robert J., Steven W. Popper, and Steven C. Bankes, "Confronting Surprise," Social Science and Computing Review, No. 4, 2002, pp. 420-440.
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Robert Lempert and Michael Schlesinger, "Adaptive Strategies for Climate Change," forthcoming Innovative Energy Strategies for CO2 Stabilization, Cambridge University Press.
Portfolio Problems:
In real life situations, decision-makers faced with extreme uncertainty should look for robust solutions, rather than a hypothetical "best" optimized for a particular set of assumptions. That is, they recognize that in a fast-changing, uncertain environment, the best can be the enemy of the good. What is required is a means to find "satisficing" solutions systematically. This case illustrates this approach applied to a portfolio problem.
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Brooks, Arthur, Steven Bankes and Bart Bennett, “An Application of Exploratory Analysis: The Weapon Mix Problem.” Military Operations Research, Vol. 4, No. 1, 1999.
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Lempert, Robert J., and James Bonomo, New Methods for Robust Science and Technology Planning, Santa Monica, Calif.: RAND DB-238-DARPA, 1998.
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"Weapons Mix and Exploratory Analysis: A Case Study," Arthur Brooks, Steven C. Bankes, and Bart Bennett, RAND, 1997.
Agent-Based Models:
Agent-based models are becoming increasingly popular in business simulation because they provide a means to incorporate important information, such as imperfect information or the diversity of preferences among consumers, that are poorly treated in more traditional modeling formalisms. However, agent-based models are difficult to employ within traditional decision-analysis frameworks and are often relegated to building intuition about a problem or "flight simulator" approaches, rather than rigorous analysis. CARs™ provides a systematic means to extract the information contained in agent-based models.
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Bankes, Steven C., “Agent-Based Modeling: A Revolution?” Proceedings of the National Academy of Sciences, Vol. 99, Supplement 3, 2002, pp. 7199-7200.
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Bankes, Steven C., “Tools and Techniques for Developing Policies for Complex and Uncertain Systems,” Proceedings of the National Academy of Sciences, Vol. 99, Supplement 3, 2002, pp. 7263-7266.
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Lempert, Robert J., “New Decision Sciences for Complex Systems.” Proceedings of the National Academy of Sciences, Vol. 99, Supplement 3, 2002, pp. 7309-7313.
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"Carrots and Sticks for New Technology: Crafting Greenhouse Gas Reduction Policies for a Heterogeneous and Uncertain World," Integrated Assessment, 1, 1-19, 2000 (David A. Robalino and Robert J. Lempert)
Scenario-Based Planning:
RAP™ combines the best features of qualitative scenario-based planning and traditional quantitative forecasting.
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