Anticipatory Activity Research Articles

Towards Understanding Future: Consistency Guided Probabilistic Modeling for Action Anticipation

Action anticipation aims to infer the action in the unobserved segment (future segment) with the observed segment (past segment). Existing methods focus on learning key past semantics to predict the future, but they do not model the temporal continuity between the past and the future. However, past actions are always highly uncertain in anticipating the unobserved future. The absence of temporal continuity smoothing in the video's past-and-future segments may result in an inconsistent anticipation of future action. In this work, we aim to smooth the global semantics changes in the past and future segments. We propose a Consistency-guided Probabilistic Model (CPM), which focuses on learning the globally temporal probabilistic consistency to inhibit the unexpected temporal consistency. The CPM is deployed on the Transformer architecture, which includes three modules of future semantics estimation, global semantics estimation, and global distribution estimation involving the learning of past-to-future semantics, past-and-future semantics, and semantically probabilistic distributions. To achieve the smoothness of temporal continuity, we follow the principle of variational analysis and describe two probabilistic distributions, i.e., a past-aware distribution and a global-aware distribution, which help to estimate the evidence lower bound of future anticipation. In this study, we maximize the evidence lower bound of future semantics by reducing the distribution distance between the above two distributions for model optimization. Extensive experiments demonstrate that the effectiveness of our method and the CPM achieves state-of-the-art performance on Epic-Kitchen100, Epic-Kitchen55, and EGTEA-GAZE.

Anticipatory action for drought in the Sahel: an innovation for drought risk management or a buzzword?

Anticipatory action is an approach that combines early warning information with flexible, pre-positioned funds to trigger actions that mitigate the impact of predictable shocks on the most vulnerable people. Historically, drought is the climatic hazard that led to the highest and most severe humanitarian impacts in the Sahel. This region, according to climate projections, will be one of the most deeply affected by climate change in future years, leading to considerable changes to societies, economies, as well as impacting rural communities. While this negative projection may lead to further increases in humanitarian consequences, recent experiences from integrating anticipatory action for drought into humanitarian practice hold positive prospects. This article will review current experiences on anticipatory action for drought in the Sahel and shed light on whether this approach has brought innovation in local disaster risk management. Through the review of recent initiatives in Burkina Faso, Chad and Niger, this paper highlights key advancements as well as gaps and challenges pertaining to key components of anticipatory action and disaster risk management, namely: (1) data, risk analysis and early warning; (2) funding; (3) preparedness and community engagement; (4) learning, coordination and partnership; (5) policies and institutional frameworks. Even in challenging environments like in the Sahel, anticipatory action for drought can become an integral component of standard disaster risk management and financing strategies. However, this process will require more robust evidence about which ingredients of anticipatory action approaches lead to the desired result.

Mechanisms of Action Anticipation in Table Tennis Players: A Multivoxel Pattern Analysis Study

An exceptional ability to accurately anticipate an opponent’s action is paramount for competitive athletes and highlights their experiential mastery. Despite conventional associations of action observation with specific brain regions, neuroimaging discrepancies persist. To explore the brain regions and neural mechanisms undergirding action anticipation, we compared distinct brain activation patterns involved in table tennis serve anticipation of expert table tennis athletes vs. non-experts by using both univariate analysis and multivoxel pattern analysis (MVPA). We collected functional magnetic resonance imaging data from 29 table tennis experts and 34 non-experts as they pressed a button to predict the trajectory of a ball in a table tennis serve video truncated at the moment of racket-ball contact vs. pressing any button while viewing a static image of the first video frame. MVPA was applied to assess whether it could accurately differentiate experts from non-experts. MVPA results indicated moderate accuracy (90.48%) for differentiating experts from non-experts. Brain regions contributing most to the differentiation included the left cerebellum, the vermis, the right middle temporal pole, the inferior parietal cortex, the bilateral paracentral lobule, and the left supplementary motor area. The findings suggest that brain regions associated with cognitive conflict monitoring and motor cognition contribute to the action anticipation ability of expert table tennis players.

Intention action anticipation model with guide-feedback loop mechanism

Anticipating human intention from videos has broad applications, such as automatic driving, robot assistive technology, and virtual reality. This study addresses the problem of intention action anticipation using egocentric video sequences to estimate actions that indicate human intention. We propose a Hierarchical Complete-Recent (HCR) information fusion model that makes full use of the features of the entire video sequence (i.e., complete features) and the features of the video tail sequence (i.e., recent features). The HCR model has two primary mechanisms. The Guide-Feedback Loop (GFL) mechanism is proposed to model the relation between one recent feature and one complete feature. Based on GFL, the MultiComplete-Recent Feature Aggregation (MCRFA) module is proposed to model the relation of one recent feature with multiscale complete features. Based on GFL and MCRFA, the HCR model can hierarchically explore the rich interrelationships between multiscale complete features and multiscale recent features. Through comparative and ablation experiments, we validate the effectiveness of our model on two well-known public datasets: EPIC-Kitchens and EGTEA Gaze+.

Adaptation pathways for effective responses to climate change risks

AbstractClimate related changes are already affecting every area of our world and will increasingly do so as global warming increases, resulting in compounding and cascading risks across multiple locations and sectors. Deliberative processes and anticipatory actions are required to adapt to the associated complex and uncertain systemic risks, with dynamic and long‐term planning needed even where there is limited knowledge of the effectiveness of adaptation. In this focus article, we examine the adaptation pathways developed for the Europe Chapter of the IPCC AR6. We argue that illustrative pathways built on quantitative and qualitative assessment of adaptation effectiveness can inform adaptation planning to manage the increasing severity of risks. We find that as the global warming level increases adaptation pathways can diverge, leading to radically different futures, for example, adaptation responses to sea level rise. We illustrate how adaptation measures for different risks interact resulting in trade‐offs, for example, increasing water scarcity. Although pathways offer a useful framework to address multiple adaptation challenges, other supporting conditions are needed for the successful implementation of adaptation, such as establishing legitimacy and buy‐in through collaboration of various actors and effective governance. Ultimately, adaptation will be increasingly more complex and constrained in a warmer world, increasing risks of losses and damages to people and nature.This article is categorized under: Vulnerability and Adaptation to Climate Change > Institutions for Adaptation The Social Status of Climate Change Knowledge > Climate Science and Decision Making Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change Vulnerability and Adaptation to Climate Change > Learning from Cases and Analogies

Cascading risks, interdependent rights, and the progression of vulnerability in the context of pandemic containment measures: Implications for anticipatory action and the humanitarian-development nexus

This paper articulates a human rights-based approach to addressing cascading risks in the context of pandemic containment measures. It sets out to highlight how the principle that human rights are interdependent and interrelated, reflected in normative standards articulated by human rights treaty body mechanisms, can inform anticipatory action and work at the humanitarian-development nexus. Grounding a human rights-based approach in the political-ecological understanding of the progression of vulnerability, it considers how lockdown interfered with the right to freedom of movement and the right to work, which in turn had cascading effects on the right to the highest attainable standard of physical and mental health, the right to adequate housing and the right to water and sanitation, amongst others. Informed by Scott et al.’s (2023) Framework for Integrating Human Rights and Gender Equality (FIRE), the paper outlines specific entry points for integrating this approach at points along the humanitarian-development nexus continuum, grounded in an appreciation of root causes, dynamic pressures and unsafe conditions characteristic of the progression of vulnerability. The article calls for pilot studies to explore the impact of an integrated human rights-based approach to cascading pandemic risk.

Differential psychophysiological responses associated with decision-making in children from different socioeconomic backgrounds.

This study examined how socioeconomic status (SES) influences on decision-making processing. The roles of anticipatory/outcome-related cardiac activity and awareness of task contingencies were also assessed. One hundred twelve children (Mage = 5.83, SDage = 0.32; 52.7% female, 51.8% low-SES; data collected October-December 2018 and April-December 2019) performed the Children's Gambling Task, while heart rate activity was recorded. Awareness of gain/loss contingencies was assessed after completing the task. Distinct decision-making strategies emerged among low and middle/high-SES children. Despite similar awareness levels between SES groups, future-oriented decision-making was linked solely to the middle/high-SES group. Somatic markers did not manifest unequivocally. However, contrasting cardiac patterns were evident concerning feedback processing and the association between anticipatory activity and awareness (low: acceleration vs. middle/high: deceleration). Results are interpreted from an evolutionary-developmental perspective.

Climate Change Impact Assessment and Disaster Risk Financing Strategies in Mali: A Comprehensive Analysis of Drought and Flood Events

Climate change impact increasingly led to humanitarian assistance increase and needed. To better address climate change impacts mitigation, a suitable financing instrument is essential to facilitate government, humanitarian, and other stakeholders' finance mobilization. However, few studies have been done on disaster risk profiling to guide decision-makers in their choices. Disaster risk profile analysis has been conducted in Mali to facilitate financial resources mobilization and climate finance instrument choice by identifying Historical drought and flood events. To do so, published papers; and some international institution websites dealing with climate hazard events such as Reliefweb, Hazard/risk, climate information services, Relief Web; CRED- EM-DAT; World Bank Climate Knowledge Portal, World Bank- UNDRR -ThinkHazard, WFP ARC/GeoNode/VAM/DataViz addressing Mali country have been assimilated for evidence accumulation and synthesis and presented in a database. Furthermore, national statistics and national reports on hazards have been also reviewed. Before starting the reading exercise, a reading/analytical framework has been elaborated. In Mali the year 1984 to 2019, 21 flood events occurred in Mali and the most exposed regions to floods are Koulikoro, Bamako and Gao. From 1969 to 2020, 21 drought events were registered in in Mali and the most affected regions are Koulikoro, Mopti, Gao, Kayes. The time return period of drought has been estimated to 3 years while the time return of flood has been estimated to be about 2 years. Drought events are less frequent than flood events, however, drought events affect more population than floods. Also, Also, the yearly response cost for drought events is USD million 277.46 with an average US USD 204.37 cost per affected population. For the flood, even the yearly response cost is USD 11.107 million With USD 261.82 per affected population. Macro-insurance and CAT bonds are more suitable disaster risk financing instruments and are recommended to better address drought events while Anticipatory action and government contingency funds are more suitable climate disaster risk financing instruments to better address flood events in Mali.

The study of water salinity distribution for supporting agriculture in Katingan I lowland irrigation area, Central Kalimantan

The Katingan I tidal lowland irrigation area (DIR Katingan I) is a sensitive area to salinity changes. This study aims to identify and estimate the spatial distribution of salinity in DIR Katingan I. The method used in this study is field measurement for collecting tidal and salinity data in the Katingan River as well as in several locations of primary and secondary canals. The measured data at the upstream canal, Katingan River, and primary canal as boundary conditions and calibration for hydraulic and water quality simulations. The simulations used HEC-RAS software to estimate salinity spatial distribution under tidal conditions at primary and secondary canals. The results showed that the distribution of water salinity can reach lower primary canals. It is necessary to take anticipatory actions to reduce the salinity intrusion. To overcome the problem, alternative recommended solutions that can be done are sluice gates installation on the lower primary canal, right primary canal, and left primary canal about 1 to 3 km from the mouth of the primary canal. The prediction of salinity spatial distribution is expected to be a useful recommendation for water management in DIR Katingan I, and it is expected to increase agricultural productivity.

Incorporating indigenous knowledge systems-based climate services in anticipatory action in Zimbabwe: an ex-ante assessment

IntroductionThe success of anticipatory action (AA) in climate change related disaster risk reduction depends largely on the ability to accurately predict adverse weather events and to subsequently take appropriate and timely action. The current seasonal climate forecasts obtained through national and global forecasting centers such as the Zimbabwe Meteorological Services Department (MSD) and the European Center for Medium-Range Weather Forecasts (ECMWF) have been found to have several limitations including limited skill in intra-seasonal variability which is vital in most processes, lack of accessibility, difficult interpretability and applicability to local communities. As a result, calls for the integration of Indigenous Knowledge Systems (IKS)-based climate services in seasonal climate forecasting to bolster the efficacy and accuracy of forecasts are increasing.MethodologyThe study employed a mixed methods approach combining a survey of 200 household heads, document reviews and key informant interviews with IKS specialists, AA community of practice members and disaster risk reduction specialists.ResultsThis article presents the findings of a study carried out in four semi-arid districts of Zimbabwe (Mbire, Matobo, Binga, and Mudzi) to assess the feasibility of integrating IKS into the drought AA mechanism at national, district, and ward level. We find that 82% of the surveyed households used indigenous knowledge systems for seasonal climate forecasting and extreme weather forecasting combined with scientific forecasts. Respondents demonstrated preference for triangulated forecasting to increase reliability. Both the meteorological approaches to seasonal climate forecasting and the IKS based forecasting had different strengths and weaknesses.DiscussionBased on the found gaps in current seasonal forecasting techniques, local applicability, and limited quantitative analysis in IKS, this study provides a guideline on how scientific and IKS forecasting can be triangulated for leveraging forecasting information in Zimbabwe. The use of IKS may be of utmost relevance to agencies and entities seeking the achievement of drought risk reduction through AA programmes.

Expert Performance in Action Anticipation: Visual Search Behavior in Volleyball Spiking Defense from Different Viewing Perspectives.

Volleyball spiking requires defenders to possess exceptional anticipatory skills. However, most volleyball defense video eye-tracking studies have used fixed or off-court perspectives, failing to replicate real-world environments. This study explored different visual search behaviors between elite and novice volleyball players from various viewing perspectives using video eye tracking. We examined spiking anticipation in 14 competitive elite, 13 semi-elite, and 11 novice players. We captured spiking videos from three on-court perspectives using GoPro cameras mounted on the defenders' heads, closely replicating real game scenarios. For comparison, we recorded baseline videos using a fixed camera. The present study revealed that competitive and semi-elite players demonstrated higher accuracy than novices. Competitive elite players used fewer fixations, indicating that their superior performance was related to stable visual search patterns. All participant groups, regardless of skill level, showed similar visual allocation among areas of interest (AOIs). However, notable differences in visual search patterns and AOI allocation were observed between baseline and on-court perspective videos. From the baseline perspective, the participants primarily utilized global perception and peripheral vision, focusing more on the setter zone or the spiker's trunk. Conversely, from the on-court perspective, they employed more fixations, focusing more intensely on the spiker's detailed movements.

Climate futures and development pathways: A journey from terrorism to tourism in the Khyber-Pakhtunkhwa Province of Pakistan

Achieving equitable development that supports climate mitigation in an uncertain future remains a daunting task, particularly for post-conflict societies. In this paper, we present results from a local stakeholder participatory scenario workshop investigating emerging priorities for anticipatory action, with respect to future climate impacts, in the vulnerable conflict-affected Khyber-Pakhtunkhwa Province of Pakistan. Importantly, our findings reveal that stakeholders were less focused on addressing climate impacts, and more interested in local development initiatives to enhance tourism offerings and the regional national park network. The novelty of our work lies in the use of participatory scenarios to both initiate a process of healing and provide a forum for the co-production of future narratives focused on sustainable and inclusive development. However, this first involves mending the social fabric that ties individuals and communities together in an inclusive and informed way. As such, our work adds to the scholarship of environmental peacebuilding, creating a local context-specific knowledge base using a bottom-up approach to understand a shared future. The case study presented here highlights the perspectives of policymakers from the global south and brings local stakeholders together in a space where top-down management approaches often dominate.

Analisis Peran Unit AMC dan Bangunan Landasan Dalam Penanganan Foreign Object Debris (FOD) di Area Apron di Bandar Udara Tunggul Wulung Cilacap

Foreign Object Debris or FOD is a foreign object that has the potential to pose a hazard to aviation safety. Supervision and maintenance of the cleanliness of the apron from the appearance of FOD is the responsibility of the Apron Movement Control (AMC) unit. This is also the responsibility of the Building and Runway unit in carrying out the function of overseeing the cleanliness of the movement area both on the land and air sides. This study aims to determine the role, constraints and anticipatory actions taken by the AMC unit and the Building and Runway unit in dealing with FOD in the apron area. This study uses qualitative research methods with data collection techniques using interviews, observation, and documentation. The type of data used is primary data in the form of the results of interviews directly with the informants, the results of observations and also documentation. There are also secondary data used such as previous research urnals, flight regulations, company documents, and other data related to research which are then processed using the triangulation method. The results of the study show that the AMC unit and the Building and Runway unit act as supervisors, controllers, and as direct follow-ups of FOD through inspection activities. The constraints experienced by the AMC unit were the lack of supporting equipment such as the absence of a follow me car, computers, CCTV, acoustic bird repellent devices, and a lack of personnel, while the constraints experienced by the Building and Runway unit were bad weather which disrupted inspection activities. As for the anticipatory actions taken, namely collaboration between units, giving directions to the flying school and routine meeting activities at the Tunggul Wulung Cilacap airport.
 Keywords: Apron Movement Control (AMC), Building and Runway units, Foreign Object Debris (FOD), Apron.

The influence of postural threat-induced anxiety on locomotor learning and updating.

The ability to adapt our locomotion in a feedforward (i.e., "predictive") manner is crucial for safe and efficient walking behavior. Equally important is the ability to quickly deadapt and update behavior that is no longer appropriate for the given context. It has been suggested that anxiety induced via postural threat may play a fundamental role in disrupting such deadaptation. We tested this hypothesis, using the "broken escalator" phenomenon: Fifty-six healthy young adults walked onto a stationary walkway ("BEFORE" condition, 5 trials), then onto a moving walkway akin to an airport travelator ("MOVING" condition, 10 trials), and then again onto the stationary walkway ("AFTER" condition, 5 trials). Participants completed all trials while wearing a virtual reality headset, which was used to induce postural threat-related anxiety (raised clifflike drop at the end of the walkway) during different phases of the paradigm. We found that performing the locomotor adaptation phase in a state of increased threat disrupted subsequent deadaptation during AFTER trials: These participants displayed anticipatory muscular activity as if expecting the platform to move and exhibited inappropriate anticipatory forward trunk movement that persisted during multiple AFTER trials. In contrast, postural threat induced during AFTER trials did not affect behavioral or neurophysiological outcomes. These findings highlight that actions learned in the presence of postural threat-induced anxiety are strengthened, leading to difficulties in deadapting these behaviors when no longer appropriate. Given the associations between anxiety and persistent maladaptive gait behaviors (e.g., "overly cautious" gait, functional gait disorders), the findings have implications for the understanding of such conditions.NEW & NOTEWORTHY Safe and efficient locomotion frequently requires movements to be adapted in a feedforward (i.e., "predictive") manner. These adaptations are not always correct, and thus inappropriate behavior must be quickly updated. Here we showed that increased threat disrupts this process. We found that locomotor actions learned in the presence of postural threat-induced anxiety are strengthened, subsequently impairing one's ability to update (or "deadapt") these actions when they are no longer appropriate for the current context.

Towards a global impact-based forecasting model for tropical cyclones

Abstract. Tropical cyclones (TCs) produce strong winds and heavy rains accompanied by consecutive events such as landslides and storm surges, resulting in losses of lives and livelihoods, particularly in regions with high socioeconomic vulnerability. To proactively mitigate the impacts of TCs, humanitarian actors implement anticipatory action. In this work, we build upon such an existing anticipatory action for the Philippines, which uses an impact-based forecasting model for housing damage based on eXtreme Gradient Boosting (XGBoost) to release funding and trigger early action. We improve it in three ways. First, we perform a correlation and selection analysis to understand if Philippines-specific features can be left out or replaced with features from open global data sources. Secondly, we transform the target variable (percentage of completely damaged houses) and not yet grid-based global features to a 0.1∘ grid resolution by de-aggregation using Google Open Buildings data. Thirdly, we evaluate XGBoost regression models using different combinations of global and local features at grid and municipality spatial levels. We first introduce a two-stage model to predict if the damage is above 10 % and then use a regression model trained on all or only high-damage data. All experiments use data from 39 typhoons that impacted the Philippines between 2006–2020. Due to the scarcity and skewness of the training data, specific attention is paid to data stratification, sampling, and validation techniques. We demonstrate that employing only the global features does not significantly influence model performance. Despite excluding local data on physical vulnerability and storm surge susceptibility, the two-stage model improves upon the municipality-based model with local features. When applied to anticipatory action, our two-stage model would show a higher true-positive rate, a lower false-negative rate, and an improved false-positive rate, implying that fewer resources would be wasted in anticipatory action. We conclude that relying on globally available data sources and working at the grid level holds the potential to render a machine-learning-based impact model generalizable and transferable to locations outside of the Philippines impacted by TCs. Also, a grid-based model increases the resolution of the predictions, which may allow for a more targeted implementation of anticipatory action. However, it should be noted that an impact-based forecasting model can only be as good as the forecast skill of the TC forecast that goes into it. Future research will focus on replicating and testing the approach in other TC-prone countries. Ultimately, a transferable model will facilitate the scaling up of anticipatory action for TCs.

One Never Knows

Abstract Understanding anticipatory action as undergirding the dynamics of life is the prerequisite for defining what art is. Its change over time reflects the fact that life is purposeful and escapes prediction. Explaining art from the perspective of means and methods involved in producing it, from a deterministic view, leads to circular reasoning: the conclusion (machine art is the future) is in the premise (machines can make art). This fallacy becomes evident in the context of the current infatuation with automation of artmaking (especially through AI), and even art evaluation. The role art plays in defining the human condition is no less significant than that of science, itself indebted to aesthetics in its expression.

Managing Multimillion-Dollar Security Budgets for Maximum ROI: Insights into Optimizing Resource Allocation to Ensure Cost-Effective Security Solutions

Allocating and disbursing large sums of money into cybersecurity is another difficult task, especially in providing the best ROI in the face of constantly emerging cyber threats. This article examines levers that can be pulled to improve the methods for determining resource allocation in strategic human resource management to increase the ROI. This stresses the need to integrate security budgets with strategic plans. Needs and risk analyses should be answered appropriately and meet the requirements of regulations. Moreover, it focuses on optimizing budgetary resources, as evidenced through quantitative data and sophisticated analytical techniques. The article further expands on the idea that technologies ranging from AI to machine learning improve the capacity for threats to be detected and managed, thus increasing the overall return on investment. It also covers some of the societal aspects of cybersecurity by noting the need to spend on cybersecurity talent acquisition and management. Contest, consolidation, and performance procurement mechanisms are considered ways of lowering the costs of cybersecurity solutions even as the quality increases due to the implementation of competitive bidding, vendor consolidation, and performance-based procuring methods. It also reveals the need to review the budget, considering the constant changes in threat, to present a bullet-proof defense mechanism. By taking anticipatory actions, keeping abreast of the threats and their actual impact through real-time threat intelligence, and analyzing and reassessing the spending plans, firms can be assured that they are equally equipped to address new risks and innovative technologies that emerge on the market. It all combines to go a long way in optimizing the Returns on Investment and, at the same time, enhances the outer security status of an organization.

Utilizing Plastic Waste with Ecobricks: Creative Solutions for A Healthy and Waste-Free Life

Indonesia ranks second as the largest producer of plastic waste in the world. Plastic waste takes about 1000 years to decompose. Cleaning up plastic waste is very difficult, because plastic waste has non-porous polymer properties, plastic can also cause temperatures to increase day by day. Plastic waste has a negative impact on the environment, such as environmental pollution due to the accumulation of waste. Anticipatory and preventive actions are needed to overcome this problem. The purpose of this research is to increase public awareness of the ecobrick method to utilize waste as an environmentally friendly material that has economic value. The research method used is a systematic literature review method, or called Systematic Literature Review (SLR) with results using an online article database

AI for Anticipatory Action: Moving beyond Climate Forecasting

Disaster response agencies have been shifting from a paradigm of climate forecasting towards one of anticipatory action: assessing not just what the climate will be, but how it will impact specific populations, thereby enabling proactive response and resource allocation. Machine learning models are becoming exceptionally powerful at climate forecasting, but methodological gaps remain in terms of facilitating anticipatory action. Here we provide an overview of anticipatory action, review relevant applications of machine learning, identify common challenges, and highlight areas where machine learning can uniquely contribute to advancing disaster response for populations most vulnerable to climate change.

Optimal defense strategies against intelligent cyber attacks

We propose a comprehensive game-theoretic model pertaining to the security of computer networks, specifically addressing the interaction between defenders and attackers. The model incorporates attack graphs to outline potential attacker strategies and defender responses. To account for the attacker's capacity to execute multiple attempts, we introduce a probabilistic element, wherein the success or failure at any arc of the attack graph is treated as stochastic. This characterization gives rise to a multi-stage stochastic network-interdiction problem. In this problem formulation, the defender strategically interdicts a set of arcs in anticipation of the likely actions of the attacker, who, in turn, can make multiple attempts to traverse the network. We mathematically articulate this scenario as a stochastic bilevel mixed-integer program with a "min-max" objective. The defender's aim is to minimize the probability of the attacker's success, while the attacker seeks to maximize the probability of successfully traversing the network across multiple attempts. The defender's stochastic bilevel optimization model is solved using the integer L-shaped method. Upon analyzing the defender's perspective, we observe the anticipated trend that the overall success probability of the attacker diminishes with an increasing level of defense. Notably, in the sensitivity analysis involving relatively small attack graphs, we discover that the optimal defense strategy against a myopic attacker often aligns with that against a non-myopic attacker. Furthermore, in instances where deviations exist, the disparity in performance is generally marginal. However, our findings demonstrate a potential divergence in optimal defense strategies when the available attack paths share numerous common arcs.