Formal Model Sample Clauses

Formal Model for describing cascading effects‌ A fundamental aspect of the method is the use of a more detailed formal model for describing cascading effects in past events, which is based on the conceptual model illustrated in Figure 3.1. Hence, additional and more specific concepts and characteristics need to be introduced. In Figure 3.3 an overview of this model is presented and in Figure 3.4 an illustration of key concepts and characteristics for a system is shown which also is used to structure the different steps of the method. The main differences between the conceptual model presented earlier and this formal model are: 1. In this model (contrary to the conceptual model presented earlier) it is sufficient that a dependency between two systems has been identified in the written account of an incident. This indicates a potential for a cascading effect but that the cascade did not take place due to some conditions being in a fortunate state. For example, due to successful flood protection of a power plant no power outage occurred. 2. The concepts of Dependency Impacts (DI) and System Impacts (SI) are introduced. a) Dependency Impacts refer to the effects on the impacted system due its dependencies to other impacted systems given some dependency conditions but excluding the impacted system’s inherent coping capacity. An example of a Dependency Impact could be that a failure in the transportation system lead to 25% of the hospital staff is not able to get to their workplace. b) System Impacts refer to the resulting effects on the impacted system due to one or several Dependency Impacts and given its inherent coping capacity and system conditions. An example of a System Impact would be that no critical surgeries can be performed due to loss of 25% of the staff since no alternative personnel can be called in. 3. The role of the impacted system’s coping capacity has been clarified. The coping capacity constitutes the system’s ability to sustain effects due to dependencies, i.

Formal Model. The Paxos protocol assumes an asynchronous distributed system in which processes com- municate by message passing. The failure model is non-byzantine, which means that pro- cesses may fail only by crashing. The system model also assumes eventually reliable links; there is a time after which every message sent by a correct process to another correct process eventually arrives (i.e. there are no message losses).

Formal Model. ‌ In this section, we describe a client’s task specification, its utility and conditions of ne- gotiation which include a negotiation protocol, the fundamental time-dependent tactics for a client and the GRA [17] and their level of knowledge about each others’ nego- tiation parameters. In the following chapters, this formal model is extended and/or modified.

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Formal Model. ‌ 4.2.1 Players and Moves‌ The model has the following players: an incumbent government (G), a village (V) located in an area of the country disputed by an insurgent movement, and a local village rival (VR). At the outset of the game, the government makes two distinct decisions with respect to CDFs. It first chooses whether to create them (CDF) or not (∼CDF). Then, having decided to create them, the government chooses the number of CDF personnel (n) village V should receive. For the sake of simplicity, its potential rival VR is located outside of the contested territory and is therefore not considered for CDF deployment. Note that this is not a critical assumption inasmuch as a model in which both villages are subject to CDF deployment would exhibit the same key dynamics. In an equilibrium in which neither village defects, the government supports both villages, and as a result neither side is propped up in their private bargaining game. By defecting, a village risks losing government support and thereby giving the opposing side a relative advantage in the private dispute. The addition of the private dispute thus renders the villages more trustworthy agents of the state. In this model, the village may be rivalrous or non-rivalrous. Before the government can decide how many CDFs V should receive, nature (N1) determines with probability p1 whether the village is rivalrous (R). Conceptually, a village is considered rivalrous when it is engaged in a dispute with VR concerning some local good or policy that has not been settled by invocation of commonly accepted law. Instead, the disputants attempt to reach an outcome by bargaining in which the threat of violent outside options exists. Formally, a rivalry is modeled as V engaging VR in a bargaining game over some good X unrelated to the overarching conflict, where any division of it x ∈ [0, 1]. The village may also have variable preferences with respect to the overarching state-vs.-insurgent conflict. Nature (N2) determines V’s bias (b), drawing randomly from a uniform distribution (b ∼ unif[0, 1]). When N2 draws a high value for b, the village receives a greater payoff from alignment with insurgents. Assuming the gov- ernment does not choose to forego CDF deployment at its first move, the magnitude of village bias will impact V’s performance of CDF duties. The government sub- sequently chooses CDF unit size for the village after N1 determines whether it is rivalrous or not and before N2 decides the magnitude of ...