Since 2004 DIMACS and LAMSADE have been running a joint research program on Computer Science and Decision Theory (see DIMACS/LAMSADE partnership). Already in October 2004, 2006 and 2008 we organized a joint workshop (see page). We are now planning a more focused workshop on Evidence Based Policy Making part of their joint project on Algorithmic Decision Theory (see more at the COST Action IC0602 and the DIMACS Special Focus on the same subject.


In recent years there has been a lot of discussion about "evidence based policy making", an approach through which policy makers should conceive policies (better policies) based on "evidence". However, despite the literature circulating on this subject, it is not crystal clear (at least for people working in the area of decision analysis, where supporting policy making is current practice) what this term evokes

and how it can influence both theory and practice within decision sciences and technologies.

What is evidence? Is it something we just have to find around us or does it have to be constructed combining information and values? Can policy making be conceived just as the result of better using information and knowledge and how values have to be taken into account? How easy is it to extract information out of the huge amounts of data today available and how easy is to transform that into evidence? How do we "measure" complex natural or social phenomena such as climate change or poverty? What happens in case such "evidence" needs to be used within some participative decision process where multiple perceptions, stakes and values need to be taken into account at the same time? Questions such as the above arise in multiple policy making situations such as conceiving adaptation and mitigation policies for climate change, policies for reducing dramatic social phenomena such as poverty, social exclusion and deviating behaviour of social groups, implementing strategies for land use and regional planning, managing natural resources under a sustainable development perspective.

The workshop aims at putting together decision and computer scientists working on the above issues under different perspectives including among others:

- how to model and construct evidence?

- how to handle extremely large amounts of information and how to extract meaningful information?

- how to combine information, knowledge and values?

- how to measure complex phenomena?

- how to develop algorithmic support for evidence-based decision making

The workshop aims at establishing a reference on how decision and computer scientists should approach evidence-based policy making both in theory and in practice and looks at:

- surveying the state of the art;

- identifying key application areas and relevant case studies;

- identifying research opportunities at a national and international level;

- setting a future research agenda.

The possibility of publishing a special issue of a major scientific journal is being considered.