Simulation-based decision support for effects-based planning

Abstract

In this paper we describe decision support and simulation techniques to facilitate effects-based planning. By using a decision support tool, a decision maker is able to test a number of feasible plans against possible courses of events and decide which of those plans is capable of achieving the desired military end state. The purpose is to evaluate plans and understand their consequences through simulating the events and producing outcomes which result from making alternative decisions. Plans are described in the effects-based approach to operations concept as a set of effects and activities that together will lead to a desired military end state. For each activity we may have several different alternatives. Together they make up all alternative plans, as an activity tree that may be simulated.Simulated plans that are similar in both their structure and consequence are clustered together by a Potts spin neural clustering method. These plans make up a robust set of similar plans that function as ready alternatives should dynamic replanning be necessary as the situation evolves.Keywords-simulation, decision support, operational planning, effects-based planning, EBP, effects-based approach to operations, EBAO.

Simulation-based decision support for evaluating operational plans

“…The behavior of an actor is in essence an action selection strategy implemented as a function that uses the actor's state variables Ω as input and generates the alternative α to execute as output, as shown in (1). For instance, if actor A attacks actor B then B might respond differently depending on its weapon power.…”

“…This process is performed by the functions g and h. Function g measures the consequence of all actions performed as a distance from the initial state S 0,0 to the current simulated state , action-by-action [1]. We have,…”

“…The internal state variables, which originate from previous work [1], are represented in this work by a vector I that contains 15 discrete state variables. The name, label (A−O), and a brief (non-exhaustive) qualitative interpretation for each variable value are presented in Table 1.…”

A stochastic discrete event simulator for effects-based planning

“…In Schubert et al (2010) we examine how high-level military plans can be modeled in order to identify the best plan alternatives. However, in this paper we focus mainly on the architectural features and information flow model of the stochastic discrete event simulator developed at the Swedish Defence Research Agency, FOI.…”

“…The idea is to have an "effects-based thinking" when designing military operations in order to reach certain effects or desired end states (Hunerwadel 2006). EBAO in general is composed by four parts: EBP for creating military plans, Effects-based Execution (EBE) which focuses on executing those plans, Effects-based Assessment (EBA) which deals with following up on the executed plans and knowledge support which provides background knowledge to the previous parts (Schubert et al 2010).…”