Complex Systems Summer School 2013-CIB Markov: Difference between revisions
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=='''Project Description'''== | =='''Project Description'''== | ||
Currently we are focused on usefully pairing the analytical tools of cross-impact balances (CIB) and Markov chains. One of the possible outputs from CIB is a succession of system states that are self-correcting, until the system arrives at a stable attractor or cyclic attractors. With current CIB software tools, there is not a very good way to visualize or investigate these successions. Markov chains could be useful for this purpose and potentially for doing additional analysis. At this stage, have not yet decided on a research question. We are thinking first about how to build tools that connect these analytical approaches. --[[User:Vanessas|Vanessas]] 02:10, 6 June 2013 (UTC) | Currently we are focused on usefully pairing the analytical tools of cross-impact balances (CIB) and Markov chains. One of the possible outputs from CIB is a succession of system states that are self-correcting, until the system arrives at a stable attractor or cyclic attractors. With current CIB software tools, there is not a very good way to visualize or investigate these successions. Markov chains could be useful for this purpose and potentially for doing additional analysis. At this stage, we have not yet decided on a research question. We are thinking first about how to build tools that connect these analytical approaches. --[[User:Vanessas|Vanessas]] 02:10, 6 June 2013 (UTC) | ||
UPDATE June 15 (from [[User:Vanessas|Vanessas]] 17:59, 15 June 2013 (UTC))<br> | |||
We now have a software tool for Gephi that permits a user to see the succession of states from a CIB analysis. At the moment, we are most interested in investigating what can be done with this tool. This may involve: | |||
*Comparing results across deterministic and probabilistic updating rules for CIB | |||
*Identifying differences in behaviors of succession under different updating rules as well as different assumptions for the stringency (or rationality) of CIB judgments | |||
*Sensitivity analysis | |||
It is also an open question how this tool relates to ideas presented in Jim Crutchfield's lectures on Information Theory. Potentially, CIB can be seen as a type of prescient rival model (if not an epsilon machine) for predicting the futures of a system of interest. Could we formalize what this tool does/represents with the notation of Information Theory? Is it useful to do so? | |||
=='''Project Progress'''== | =='''Project Progress'''== | ||
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*Consider visualizations for results (all group members; Hua to spearhead?) | *Consider visualizations for results (all group members; Hua to spearhead?) | ||
*Consider connections to information theory? (Vanessa and Matteo to spearhead) | *Consider connections to information theory? (Vanessa and Matteo to spearhead) | ||
*Work on final presentation (slides and paper; all group members to do) | *Work on final presentation (slides and paper; all group members to do. ''Google doc now available!'') | ||
Latest revision as of 13:11, 17 June 2013
Complex Systems Summer School 2013 |
Project Description
Currently we are focused on usefully pairing the analytical tools of cross-impact balances (CIB) and Markov chains. One of the possible outputs from CIB is a succession of system states that are self-correcting, until the system arrives at a stable attractor or cyclic attractors. With current CIB software tools, there is not a very good way to visualize or investigate these successions. Markov chains could be useful for this purpose and potentially for doing additional analysis. At this stage, we have not yet decided on a research question. We are thinking first about how to build tools that connect these analytical approaches. --Vanessas 02:10, 6 June 2013 (UTC)
UPDATE June 15 (from Vanessas 17:59, 15 June 2013 (UTC))
We now have a software tool for Gephi that permits a user to see the succession of states from a CIB analysis. At the moment, we are most interested in investigating what can be done with this tool. This may involve:
- Comparing results across deterministic and probabilistic updating rules for CIB
- Identifying differences in behaviors of succession under different updating rules as well as different assumptions for the stringency (or rationality) of CIB judgments
- Sensitivity analysis
It is also an open question how this tool relates to ideas presented in Jim Crutchfield's lectures on Information Theory. Potentially, CIB can be seen as a type of prescient rival model (if not an epsilon machine) for predicting the futures of a system of interest. Could we formalize what this tool does/represents with the notation of Information Theory? Is it useful to do so?
Project Progress
To-do list, June 16-22
- Test code developed by Stephan & Alastair ("kicking the tires"; all group members to do)
- Consider research questions/results to discuss in presentation (all group members; Vanessa to spearhead)
- Consider visualizations for results (all group members; Hua to spearhead?)
- Consider connections to information theory? (Vanessa and Matteo to spearhead)
- Work on final presentation (slides and paper; all group members to do. Google doc now available!)
To-do list, June 6-9
- Vanessa to upload tutorial slides to wiki
- Stephane and Alastair to look at ScenarioWizard software/code, develop strategy for CIB-Markov tool development
- Vanessa and Hua (and others?) to brainstorm initial simple test cases for tool development