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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| Analysis of competing hypotheses | 2/2 | https://en.wikipedia.org/wiki/Analysis_of_competing_hypotheses | reference | science, encyclopedia | 2026-05-05T09:58:59.135316+00:00 | kb-cron |
ACH demands that the analyst makes too many discrete judgments, a great many of which contribute little if anything to discerning the best hypothesis ACH misconceives the nature of the relationship between items of evidence and hypotheses by supposing that items of evidence are, on their own, consistent or inconsistent with hypotheses. ACH treats the hypothesis set as "flat", i.e. a mere list, and so is unable to relate evidence to hypotheses at the appropriate levels of abstraction ACH cannot represent subordinate argumentation, i.e. the argumentation bearing up on a piece of evidence. ACH activities at realistic scales leave analysts disoriented or confused. Van Gelder proposed hypothesis mapping (similar to argument mapping) as an alternative to ACH.
=== Structured analysis of competing hypotheses === The structured analysis of competing hypotheses offers analysts an improvement over the limitations of the original ACH. The SACH maximizes the possible hypotheses by allowing the analyst to split one hypothesis into two complex ones. For example, two tested hypotheses could be that Iraq has WMD or Iraq does not have WMD. If the evidence showed that it is more likely there are WMDs in Iraq then two new hypotheses could be formulated: WMD are in Baghdad or WMD are in Mosul. Or perhaps, the analyst may need to know what type of WMD Iraq has; the new hypotheses could be that Iraq has biological WMD, Iraq has chemical WMD and Iraq has nuclear WMD. By giving the ACH structure, the analyst is able to give a nuanced estimate.
=== Other approaches to formalism === One method, by Valtorta and colleagues uses probabilistic methods, adds Bayesian analysis to ACH. A generalization of this concept to a distributed community of analysts lead to the development of CACHE (the Collaborative ACH Environment), which introduced the concept of a Bayes (or Bayesian) community. The work by Akram and Wang applies paradigms from graph theory. Other work focuses less on probabilistic methods and more on cognitive and visualization extensions to ACH, as discussed by Madsen and Hicks. DECIDE, discussed under automation is visualization-oriented. Work by Pope and Jøsang uses subjective logic, a formal mathematical methodology that explicitly deals with uncertainty. This methodology forms the basis of the Sheba technology that is used in Veriluma's intelligence assessment software.
== Software ==
A few online and downloadable software tools help automate the ACH process. These programs leave a visual trail of evidence and allow the analyst to weigh evidence.
PARC ACH 2.0 was developed by Palo Alto Research Center (PARC) in collaboration with Richards J. Heuer, Jr. It is a standard ACH program that allows analysts to enter evidence and rate its credibility and relevance. Decision Command software was developed by Willard Zangwill. DECIDE was developed by the analytic research firm SSS Research, Inc. DECIDE not only allows analysts to manipulate ACH, but it provides multiple visualization products. Analysis of Competing Hypotheses (ACH) is an open-source ACH implementation. ACH Template is an Excel sheet that implements the scoring and weighting methodology of ACH, more specifically the weighted inconsistency counting algorithm.
== See also ==
== Notes ==