- Award ID(s):
- 1919453
- PAR ID:
- 10456126
- Date Published:
- Journal Name:
- ICASP14 - 14th International Conference on Applications of Statistics and Probability in Civil Engineering
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
The value of information (VoI) provides a rational metric to assess the impact of data in decision processes, including maintenance of engineering systems. According to the principle that “information never hurts”, VoI is guaranteed to be non-negative when a single agent aims at minimizing an expected cost. However, in other contexts such as non-cooperative games, where agents compete against each other, revealing a piece of information to all agents may have a negative impact to some of them, as the negative effect of the competitors being informed and adjusting their policies surpasses the direct VoI. Being aware of this, some agents prefer to avoid having certain information collected, when it must be shared with others, as the overall VoI is negative for them. A similar result may occur for managers of infrastructure assets following the prescriptions of codes and regulations. Modern codes require the probability of some failure events be below a threshold, so managers are forced to retrofit assets if that probability is too high. If the economic incentive of those agents disagrees with the code requirements, the VoI associated with tests or inspections may be negative. In this paper, we investigate under what circumstance this happens, and how severe the effects of this issue can be.more » « less
-
The Value of Information (VoI) assesses the impact of data in a decision process. A risk-neutral agent, quantifying the VoI in monetary terms, prefers to collect data only if their VoI surpasses the cost to collect them. For an agent acting without external constraints, data have non-negative VoI (as free “information cannot hurt”) and those with an almost-negligible potential effect on the agent's belief have an almost-negligible VoI. However, these intuitive properties do not hold true for an agent acting under external constraints related to epistemic quantities, such as those posed by some regulations. For example, a manager forced to repair an asset when its probability of failure is too high can prefer to avoid collecting free information about the actual condition of the asset, and even to pay in order to avoid this, or she can assign a high VoI to almost-irrelevant data. Hence, by enforcing epistemic constraints in the regulations, the policy-maker can induce a range of counter-intuitive, but rational, behaviors, from information avoidance to over-evaluation of barely relevant information, in the agents obeying the regulations. This paper illustrates how the structural properties of VoI change depending on such external epistemic constraints, and discusses how incentives and penalties can alleviate these induced attitudes toward information.more » « less
-
null (Ed.)We develop computable metrics to assign priorities for information collection on binary systems composed of binary components. Components are worth inspecting because their condition states are uncertain, and system functioning depends on them. The Value of Information (VoI) enables assessment of the impact of information in decision making under uncertainty, including the component’s reliability and role in the system, the precision of the observation, the available maintenance actions and the expected economic loss. We introduce the VoI-based metrics for system-level (“global”) and component-level (“local”) maintenance actions, analyze the properties of these metrics, and apply them to series and parallel systems. We discuss their computational complexity in applications to general network systems and, to tame the complexity for the local metric assessment, we present a heuristic and assess its performance on some case studies.more » « less
-
The age of information (AoI) is now well established as a metric that measures the freshness of information delivered to a receiver from a source that generates status updates. This paper is motivated by the inherent value of packets arising in many cyber-physical applications (e.g., due to precision of the information content or an alarm message). In contrast to AoI, which considers all packets are of equal importance or value, we consider status update systems with update packets carrying values as well as their generated time stamps. A status update packet has a random initial value at the source and a deterministic deadline after which its value vanishes (called ultimate staleness). In our model, the value of a packet either remains constant until the deadline or decreases in time (even after reception) starting from its generation to the deadline when it vanishes. We consider two metrics for the value of information (VoI) at the receiver: sum VoI is the sum of the current values of all packets held by the receiver, whereas packet VoI is the value of a packet at the instant it is delivered to the receiver. We investigate various queuing disciplines under potential dependence between value and service time and provide closed form expressions for both average sum VoI and packet VoI at the receiver. Numerical results illustrate the average VoI for different scenarios and relations between average sum VoI and average packet VoI.
-
Optimal exploration of engineering systems can be guided by the principle of Value of Information (VoI), which accounts for the topological important of components, their reliability and the management costs. For series systems, in most cases higher inspection priority should be given to unreliable components. For redundant systems such as parallel systems, analysis of one-shot decision problems shows that higher inspection priority should be given to more reliable components. This paper investigates the optimal exploration of redundant systems in long-term decision making with sequential inspection and repairing. When the expected, cumulated, discounted cost is considered, it may become more efficient to give higher inspection priority to less reliable components, in order to preserve system redundancy. To investigate this problem, we develop a Partially Observable Markov Decision Process (POMDP) framework for sequential inspection and maintenance of redundant systems, where the VoI analysis is embedded in the optimal selection of exploratory actions. We investigate the use of alternative approximate POMDP solvers for parallel and more general systems, compare their computation complexities and performance, and show how the inspection priorities depend on the economic discount factor, the degradation rate, the inspection precision, and the repair cost.