Scientific achievements in 2013

The Advanced System Analysis (ASA) Program’s primary mission of developing novel methods and systems-analytic techniques puts it at the core of cross-cutting research, with researchers contributing to all three IIASA main research areas as well as to research on the drivers of global transformation.

Abstract human eye

In dynamic systems, control, and optimization theoretical and numerical advances related to the Pontryagin maximum principle were made, long-term economic growth models analyzed, and on optimal heterogeneous resource consumption studied.

In multiple objectives, trade-offs, and games, ASA completed development of a user-friendly prototype software tool for Multiple-Criteria Model Analysis (MCMA), revealed the co-benefits of key energy sustainability objectives, and designed decision-support system (DSS) with multiple objectives.

In research into systemic risk and networks, ASA looked at systems marked by interlinkages and interdependencies, where failure of one entity or a cluster of entities can cause a cascading failure capable of bringing down an entire system.

In uncertainty, resilience, risk and robust solutions, researchers focused on the resilience of ecosystems and ecosystem services, and studied the resilience of socioeconomic networks.

In the methodological area of integrated modeling and qualitative analysis, ASA analyzed different methodological approaches to model integration.

Advances were made in stochastic downscaling, with identification of structural changes in time series of socio-ecological transitions, and analyzing “big data" sets in the methodological area of artificial intelligence and data analysis.

In work related to simulations and agent-based modeling, techniques were reviewed for characterizing the performance of environmental models.

Artificial intelligence and data analysis

Advances were made in 2013 by the Advanced Systems Analysis (ASA) Program in stochastic downscaling, identifying structural changes in time series of socio-ecological transitions, and analyzing “big data" sets. More

Dynamic systems, control, and optimization

The Advanced Systems Analysis (ASA) Program's study of dynamical systems, control, and optimization, is based on understanding the heterogeneous interactions of the parts of large socioeconomic systems that function across many sectors and are driven by multiple agents. More

Integrated modeling and qualitative analysis

As environmental problems do not respect disciplinary boundaries, integrated assessment modeling, pioneered by IIASA, is a useful adjunct to environmental policy analysis, integrating knowledge from more than one domain into a single framework. More

Multiple objectives, tradeoffs, and games

In multiple objectives, trade-offs, and games, development of a user-friendly prototype software tool for Multiple-Criteria Model Analysis (MCMA) was completed, the co-benefits of key energy sustainability objectives were revealed, and decision-support system (DSS) with multiple objectives of energy users, producers, and legislative authorities were designed. More