000242741 001__ 242741
000242741 005__ 20230219174821.0
000242741 0247_ $$2CORDIS$$aG:(EU-Grant)101002240$$d101002240
000242741 0247_ $$2CORDIS$$aG:(EU-Call)ERC-2020-COG$$dERC-2020-COG
000242741 0247_ $$2originalID$$acorda__h2020::101002240
000242741 035__ $$aG:(EU-Grant)101002240
000242741 150__ $$aThe Patterns of Conflict Emergence: Developing an Automated Pattern Recognition System for Conflict$$y2022-01-01 - 2026-12-31
000242741 372__ $$aERC-2020-COG$$s2022-01-01$$t2026-12-31
000242741 450__ $$aPaCE$$wd$$y2022-01-01 - 2026-12-31
000242741 5101_ $$0I:(DE-588b)5098525-5$$2CORDIS$$aEuropean Union
000242741 680__ $$aAre there recurring patterns in the escalation and emergence of wars? The idea that history may repeat itself is old. But
recent advances overcoming methodological and data barriers present an opportunity to identify these recurrences
empirically and to examine whether these patterns can be classified to improve forecasts and inform theories of conflict. I
propose to combine new methods—using the shape of the sequence of events rather than its raw values—and novel data
on conflict from finance, diplomatic cables, and newspapers, to extract typical pre-war motifs. Just as DNA sequencing has
been critical to medical diagnoses, PaCE aims to diagnose international politics by uncovering the relevant patterns in the
area of conflict. Our goals are to:
(i) Identify patterns in the pre-conflict actions using data on conflict events—from the onset of WWI to Hamas’s rocket
launches—and in their perceptions using data from financial markets (the “crowd’s” perception), news articles (the “experts”),
and diplomatic documents (the policy-makers). This will allow us to evaluate the patterns of escalation over different
timescales—from the decade to the minute. The similarity between temporal sequences will be measured using algorithms
which allow for flexible matching, such as Dynamic Time Warping.
(ii) Evaluate the utility of these patterns to improve forecasts of conflict with both historical and live out-of-sample
predictions. Our results, using shape-based classification methods, will be made public and evaluated in real time. Moreover,
using new measures of complexity to distinguish regular, chaotic, and random behavior, I will measure possible fundamental
limits to the predictability of conflict events.
(iii) Summarize the core features of dangerous patterns into motifs—recurring patterns—that can help build new
theories of conflict emergence and escalation. PaCE will build a repository of shapes—a grammar of patterns—to be used
as the building blocks of new theories.
000242741 909CO $$ooai:juser.fz-juelich.de:899181$$pauthority$$pauthority:GRANT
000242741 909CO $$ooai:juser.fz-juelich.de:899181
000242741 980__ $$aG
000242741 980__ $$aCORDIS
000242741 980__ $$aAUTHORITY