Principles and models of expert-analytical methodology for adaptive organizational decisions forming under deep uncertainty

The paper depicts and analyzes Expert-Analytical Methodology named EAM DMDU to support Proactive Anti-crisis Decisions within Organizational Systems under deep uncertainty. Complex tools are proposed for Domain Knowledge analytical operation. Benefit is no essential resource demands while keeping the basic principles deal with uncertainty (uncertainties inconsisten- cies eliciting; Decision vulnerabilities searching instead prediction; threats resilience priority over effectiveness). enables Deliberative multi-staged Process Adaptive forming aimed at expected future conflict situation solving. stages are: Problem Analysis, Impact on Situation Goal Proposition, proposals Assessment; Efforts achieving Proposals; Effort Proposals reference Proposal option Selection adaptations accordingly Frame changes Recommendation. operation enabled procedures such as: formal analysis, individual expert assessment, elements deliberative forming. common information space of based Ontology ensures equal participants’ awareness, judgments their arguments constructive representation knowledge reuse. Expert-analytical uses Perspectivity Model. It a sub-goals hierarchy achieve goal being formed previous stages. Hierarchy knot represented ontologically formalized definition State Art corresponding sub-goal achievement. Leaf node explicit Estimates Certainty factor (from Stanford model) provided concerning its implementation through element assessed. Estimate’s used by expert. Under incomplete certainty provides boundary values estimates both pessimistic optimistic. Model contains also conditions achievement violation caused environmental threats. Procedures integration up provide extreme Robustness regarding current unsatisfactory properties integrated adjustment carried out using Uncertainty Map provided. final selected Goal-Means guides adapt it when decision frame changes. Further research instrumental development usage defense management.