Conflict Analysis Model Research Articles

Multi-modal and multi-criteria conflict analysis model based on deep learning and dominance-based rough sets: Application to clinical non-parallel decision problems

The non-parallel disease progression and curative effect are the difficulties of clinical diagnosis and treatment decisions. Experts (doctors) constantly summarize these non-parallel phenomena for more accurate diagnosis and treatment. In order to discover the mechanism of clinical non-parallel decision-making, this paper constructs a multi-modal and multi-criteria conflict analysis method based on deep learning (DL) and dominance-based rough sets (DRSA). First, for multi-modal attribute information, we adopted a deep learning based visual attention distribution to focus on the priority areas of images, a deep residual network is used for a feature extractor. The dominant characteristics of the attributes are considered, and the dominant similarity relationship based on cosine similarity is constructed using DRSA. Second, conditional attributes are used to classify objects and predict clinical progression (outcome). At the same time, the objects are classified according to decision attributes based on DRSA. Third, the Pawlak conflict analysis is introduced to analyze the consistency between the predicted results of conditional attributes and the practical results generated by decision attributes. Finally, four clinically non-parallel decision datasets are used, including colorectal cancer (CRC), membranous nephropathy (MN), rheumatoid arthritis (RA) diagnosis and MN efficacy evaluation, to verify the applicability and validity of the proposed model and discover the non-parallel decision mechanism of different diseases. This paper constructs a data-driven clinical decision research paradigm, and provides a research approach to a wide range of non-parallel decision-making problems.

A game theoretic conflict analysis model with linguistic assessments and two levels of game play

In a conflict scenario, the domestic and international stake holders vye to safeguard their specific vested interests and objectives, like in the Syrian and Afghan conflicts. Knowledge about the position of domestic players can help both domestic and international players determine the root causes of conflict and work in groups to resolve the divergent issues. Due to complex nature of conflicts, it is pertinent to study conflict at domestic and international levels separately. For this purpose, we design a two-level conflict analysis model based on game theory and linguistic assessments of players. The first level deals with local players by playing a game between each of them in view of local issues and taking into account the local grouping. At the second level, game is played between local groups and international players regarding multiple issues. In this way, all the parties calculate the gains or losses of comparable actions of each other. Thus, the proposed model provides a comprehensive study of conflict. This paper studies Syrian conflict to validate the conflict analysis algorithm and explain the computations and results.

Weighted three-way conflict analysis in multi-attribute decision-making perspective

In real life, multiple issues may have different weights in leading to conflicts. Some of the existing conflict analysis literature related to weight does not involve an explicit weight method, and some use common methods such as entropy weight method. This paper aims to design a reasonable weighting method for the inherent characteristics of conflict analysis. The main motivation is that the issues getting vast majority of support (or opposition) are assumed to be more likely to cause intense conflicts. Firstly, a novel weighting method using N-bounded symmetric concave reciprocal function is brought in. Some properties of the method such as duality, objectivity and symmetry are discussed. Then, by embedding the weights into the existing distance function a weighted three-way conflict analysis model is proposed. Next the thresholds of conflict, alliance and neutrality relations are given by decision-theoretic rough set theory. In addition, as a main characteristic of the model, the conflict distance between any two agents is determined by the overall conflict table rather than their own. Finally, the model of this paper is compared with the existing conflict analysis weight model. At the same time, a comparative simulation experiment was carried out on the weight change and the number of maximal coalitions. The new weighted conflict model proposed in this paper can effectively compensate for the limitations of existing weighted models, especially in three-valued information systems and multi-valued information systems. It can also theoretically expand the field of three-way conflict analysis.

Three-way conflict analysis model under agent-agent mutual selection environment

Conflict analysis is an effective methodology for comprehensively analyzing conflicts. Utilizing Pawlak's rough set theory, the traditional conflict analysis model investigates the origins of conflict by evaluating agents' positions on various issues and provides feasible solutions to resolve conflicts. However, it predominantly centers on the conflicts within a single agent set and fails to address the case of conflicts between two agent sets under mutual selection environment (called agent-agent mutual selection), which also frequently appears in the real world. Different from the traditional conflict analysis model, in agent-agent mutual selection, conflicts not only originate between two agents within a set due to their common preference but also originate between two agent sets due to their attitudes on a pairing strategy. Therefore, the issue of agent-agent mutual selection requires simultaneously considering the preference of two agent sets. To study this problem, we propose a three-way conflict analysis model to analyze agent-agent mutual selection. The model not only reveals the internal causes of conflicts between two agents in a set but also explores the degree of conflict between two sets of agents. A method to minimize the conflict between two sets of agents is also designed by maximizing the satisfaction degree (SD) of the valid pairing. Experiments indicate that the satisfaction degree (SD) derived from the agent-agent conflict analysis model exceeds that of the agent-issue conflict analysis model.

Grey conflict analysis approach with constraints

PurposeWe attempt to construct a grey three-way conflict analysis model with constraints to deal with correlated conflict problems with uncertain information.Design/methodology/approachIn order to address these correlated conflict problems with uncertain information, considering the interactive influence and mutual restraints among agents and portraying their attitudes toward the conflict issues, we utilize grey numbers and three-way decisions to propose a grey three-way conflict analysis model with constraints. Firstly, based on the collected information, we introduced grey theory, calculated the degree of conflict between agents and then analyzed the conflict alliance based on the three-way decision theory. Finally, we designed a feedback mechanism to identify key agents and key conflict issues. A case verifies the effectiveness and practicability of the proposed model.FindingsThe results show that the proposed model can portray their attitudes toward conflict issues and effectively extract conflict-related information.Originality/valueBy employing this approach, we can provide the answers to Deja’s fundamental questions regarding Pawlak’s conflict analysis: “what are the underlying causes of conflict?” and “how can a viable consensus strategy be identified?”

A lattice-theoretic model of three-way conflict analysis

Pawlak conflict analysis uses a three-valued situation table for representing the ratings of a set of agents on a set of issues. This paper examines a lattice-theoretic basis of three-way conflict analysis. Qualitatively, we adopt a triangle, namely, an MS.F-bilattice, to characterize the structures of agents ratings, which gives an intuitive and effective tool for ordering a single agent and a pair of agents. We consider a strength ordering and a rating ordering to construct MS.F-bilattices. By applying the principles of three-way decision as thinking in threes, we trisect, according to the rating ordering, the nine pairs of ratings into three regions: potential opposition (PO), potential conflict (PC), and potential support (PS) regions. For each region, according to the strength ordering, we construct the weak, medium, and strong three subregions. Quantitatively, we introduce opposition-alliance and support-alliance measures based on the rating ordering for one issue to trisect these pairs of ratings into PO, PC, and PS regions. We study opposition strength, conflict strength, and support strength measures based on strength ordering for one issue to trisect each of the three regions into three subregions. Finally, we extend the five types of measures for a set of issues. The lattice-theoretic model of three-way conflict analysis clarifies the semantics of pairs of ratings by two agents and gives a different perspective on trisection methods in conflict analysis. To demonstrate the value of the proposed methods, we analyze a case study of the development planning of the Gansu Province of China.

Conflict Analysis Triggered by Three-Way Decision and Pythagorean Fuzzy Rough Set

Conflict is ubiquitous in human society and has a profound impact on various fields such as the economy, politics, law, and military. Many scholars have focused on exploring the internal mechanisms and potential solutions to conflicts. Notably, describing agents’ attitudes is an effective way to construct a conflict model. However, in decision-making, agents’ attitudes on issues are often vague and ambiguous. Pythagorean fuzzy set can deal with fuzzy information more accurately than intuitionistic fuzzy set. On the basis of this understanding, we investigate the conflicts from the perspective of Pythagorean fuzzy set. Firstly, we use Pythagorean fuzzy numbers to express the attitudes of agents on issues, and subsequently establish a Pythagorean fuzzy conflict information system. Secondly, we classify agents into three categories by a pair of thresholds to establish a trisected agent set model with risk preference. Thirdly, we construct a three-way conflict analysis model based on multi-granulation Pythagorean fuzzy decision-theoretic rough set and discuss both global and local conflicts by combining conflict analysis with multi-granulation decision-theoretic rough set. Finally, we discuss the relationships and properties of the proposed conflict analysis models.

Weighted continuous triangular fuzzy conflict analysis and its three-way decision method1

In the existing conflict analysis models, they used a triangular fuzzy number on [0, 1] to describe the range of an agent’s attitude towards an issue, but there are still some shortcomings in describing the specific attitude and degree of conflict represented by the triangular fuzzy number. In this paper, the conflict analysis model is extended, improved and perfected. Firstly, the expectation of triangular fuzzy number is used in the [-1, 1] triangular fuzzy information system to reasonably express the specific attitudes represented by a triangular fuzzy number. Secondly, the weights of each issue are obtained by using the Sugeno measure, which determines the total attitude of the agent towards all issues. Thirdly, the relationship between agents is obtained with the help of the weighted distance of triangular fuzzy numbers. Finally, the thresholds α and β are calculated by means of triangular fuzzy decision theory rough sets.

A three-way conflict analysis model with decision makers’ varying preferences

The preferences of decision makers (DMs) over conflicting states have a significant impact on the stability of the conflict system. However, the DM’s preferences over conflicting states are generally unclear and variable, as they are influenced by the unpredictability of future situations of nature and the psychological behavior of DMs. To deal with multi-issue conflict problems, since the interval grey number and three-way decisions can reveal the mechanism of DMs’ grey and varying preferences in uncertain natural situations, we exploit grey system theory, conflict analysis, and three-way decisions to establish a novel conflict analysis model with varying decision makers’ preferences, and a conflict case of industry-university-research innovation alliance verifies the efficacy and rationality of the model.

A dynamic three-way conflict analysis model with adaptive thresholds

Three-way conflict analysis model, based on information systems, is about trisecting, getting coalitions and decision-making. Since the model is proposed by Yao, many models have been proposed to enrich the field of three-way conflict analysis. In this paper, we propose a new three-way conflict analysis model. Our work can be divided into four parts. First, we define new fuzzy granules and an new approximation operator to obtain better trisections. Second, we introduce dynamic information systems which are generalizations of classical information systems. The new information systems enable us to induce trisections dynamically. Third, a new Bayesian algorithm is proposed for thresholds-computing which plays an important role in inducing trisections. In the classical Bayesian approach, there are six original parameters given subjectively. And in our algorithm, the parameters are replaced by three centers and a distance measure. Finally, our new model is applied to tourism planning in two cases, one can be presented by a dynamic information system and the other one can be presented by a dispersed information system generalized from dynamic information system.

Resolving Agent Conflicts Using Enhanced Uncertainty Modeling Tools for Intelligent Decision Making

Conflict analysis in intelligent decision making has received increasing attention in recent years. However, few researchers have analyzed conflicts by considering trustworthiness from the perspective of common agreement and common opposition. Since L-fuzzy three-way concept lattice is able to describe both the attributes that objects commonly possess and the attributes that objects commonly do not possess, this paper introduces an L-fuzzy three-way concept lattice to capture the issues on which agents commonly agree and the issues which they commonly oppose, and proposes a hybrid conflict analysis model. In order to resolve conflicts identified by the proposed model, we formulate the problem as a knapsack problem and propose a method for selecting the optimal attitude change strategy. This strategy takes into account the associated costs and aims to provide the decision maker with the most favorable decision in terms of resolving conflicts and reaching consensus. To validate the effectiveness and feasibility of the proposed model, a case study is conducted, providing evidence of the model’s efficacy and viability in resolving conflicts.

Regret theory based three-way conflict analysis model under q-rung orthopair fuzzy information: studies with parameter and three-way decision-making-based approaches

Regret theory based three-way conflict analysis model under q-rung orthopair fuzzy information: studies with parameter and three-way decision-making-based approaches

The resolution of q-rung orthopair fuzzy set based three-way group conflict analysis

In social life, conflict situations occur frequently all the time. To analyse a conflict situation, not only the intrinsic reason of the conflict but also the resolution of the conflict should be given. In this paper, we propose a combine conflict analysis model under q-rung fuzzy orthopair information system that contain conflict resolution, which is called discern function-based three-way group conflict analysis. Firstly, we propose three novel form conflict distances which are induced by discern functions, and examine their properties, then the comprehensive conflict distances are given based on the normality and symmetry they share. Thus, the conflict analysis and resolution method in our model can be directly gained based on these novel form conflict distances. Secondly, from the view of group decision, the comprehensive q-rung fuzzy loss function is attained by aggregating a group of q-rung fuzzy loss functions through the q-rung orthopair fuzzy weighted averaging operator in the procedure of conflict resolution. Finally, we employ an example of the governance of a local government to demonstrate the process of finding an optimal feasible strategy in our model.

Three-way conflict analysis and resolution based on q-rung orthopair fuzzy information

In solving some complex conflict problems, compared with intuitionistic fuzzy sets (IFSs) and Pythagorean fuzzy sets (PFSs), q-rung orthopair fuzzy sets (q-ROFSs) can better express and model imprecise information. In addition, three-way decisions (TWDs), an emerging theory of simulating human decision-making behavior, play an increasingly important role in the study of conflict problems. In order to solve conflict problems under q-rung orthopair fuzzy information (q-ROFI), we propose a three-way conflict analysis and resolution model based on TWDs and decision-theoretic rough sets (DTRSs) theory, which provides another answer for Deja's fundamental questions about Pawlak's conflict model, namely, “what are the inherent causes of conflict?” and “how can a viable strategy be found?” different from the existing ones. To be specific, firstly, we define new conflict distances and conflict function for q-ROFI system using aggregation functions and weight determination method, and prove some of their properties. On this basis, the concepts of three-level of contention set and agent set, a trisection of conflict set under individual contention and contention set, and maximum doughty coalition of q-ROFI are introduced. Secondly, after introducing the rough approximation threshold calculation method on the basis of standard evaluation set, to find the optimal viable strategy under the given q-ROFI, we calculate and sort the score function by the upper and lower approximation operators in the proposed q-rung orthopair fuzzy decision-theoretic rough sets (q-ROFDTRSs) model. Thirdly, we use the proposed model to study a land-use conflict case in a metropolitan area to verify the feasibility. Finally, from sensitivity and comparative analysis, we verify the stability and validity of the q-ROFDTRSs model.

Three-way conflict analysis based on hybrid situation tables

The existing studies about three-way conflict analysis are based on a single type of situation tables. However, due to the complexity and uncertainty of the objective world, the rating types in a situation table may be diverse. We call this kind of situation table as a hybrid situation table. In this paper, we focus on three-way conflict analysis based on hybrid situation tables. First of all, we propose the conception of hybrid situation tables. By aggregating conflict distances for a single type of rating, we give the conception of hybrid conflict distances in a hybrid situation table. On this basis, we establish a three-way conflict analysis model w.r.t. multiple issues based on hybrid situation tables. Secondly, we define (maximal) strong alliances, (maximal) weak alliances, and maximal alliances, which can help to find a conflict resolution method in a hybrid situation table. In order to resolve conflict, we define feasible strategies in a hybrid situation table and use interval-valued decision-theoretic rough sets to approximate maximal strong alliances w.r.t. feasible strategies. Besides, we propose the conception of evaluation functions for finding an optimal strategy. Finally, we explore a governance problem of government to illustrate the validity and feasibility of the proposed method.

Small Wars of the Great Powers: Charles Edward Callwell and the Russian Empire in Comparative Perspective

In this article the author focuses on the semantic and substantive aspects of the colonial conflict analysis model presented in the work of the British Army Major General Charles Edward Collwell, “Small Wars: Their Principles and Practices”, which became the most notable British treatise on the subject at the turn of the nineteenth and twentieth centuries. A distinctive feature of the work is the comparative approach to the analysis of the British colonial wars fought in the Victorian era. It is established that the Russian case (the annexation of Central Asia and the pacification of the North Caucasus) is a golden thread running through all sections of the work, serving, along with similar examples from French, Spanish, and US history, as a kind of tuning fork for the universal principles of successful small warfare that Callwell laid out in his work. The aim of the paper is to form a more substantive account of the significance of comparative colonialism for British military thinking and the place of the Russian experience in its evolution. The study has shown that “Small Wars” reflected a course towards the normalisation of the Russian Empire within a professional discourse. In addition, the historiography focuses on Callwell's selective approach to the choice of factual material and its place in the evolution of British counterinsurgency. In this article, the author focuses on identifying the reasons for differences in the forms and ways of systematizing the experience of small wars in the colonial and frontier policies of both the Russian and British empires. Particular attention is paid to the circumstances that led to the gradual loss of Callwell's work to its former importance on the eve and after the Great War.

Restorative Justice and Peace Creation in Western Kenya

The article assesses the use of indigenous methods of conflict resolution embedded in restorative practices and seeks to establish the role that Mount Elgon’s Residents Association played in peace-building in the area. The study adopts the theoretical work of Johan Galtung’s conflict analysis model and John Paul Lederach’s conflict transformation work on peace-building. The study reveals a yawning need for younger community members to be more involved in peace-building activities in the Mt Elgon area. It further reveals that community members aged between 35 and 54 years strongly believe that their traditional culture and indigenous practices is central to their peace-building efforts in their locality. The study found out that a majority of community members felt that their involvement has played an important role in disarming local militia groups and in peace-building. Overall, the community strongly pointed at land and “dirty politics” as issues being at the forefront of community conflict in Mt. Elgon.

Multilevel Conflict Analysis Based on Fuzzy Formal Contexts

Uncertainties are widespread in real-world situations. In the existing studies, the uncertainties expressed by the agents engaged in a conflict situation have been extensively investigated. However, to what extent these agents can be trusted is often ignored and seldom taken into account. In this article, to manage these two sides of uncertainties, we propose a mathematical framework for multilevel conflict analysis from an outsider's perspective. Concretely, in order to indicate the analysis levels and manage the conflict situation with an extent-intent view, we resort to fuzzy formal concept analysis. At first, we explain what is multilevel data analysis. After that, based on fuzzy concept lattices, we present a general framework for multilevel conflict analysis and a method for computing the maximal coalitions and minimum conflict sets. And then, we describe how to update conflict analysis results when increasing analysis levels. Experimental analysis demonstrates that managing two sides of uncertainties can bring much more conflict resolution, and increasing analysis levels is helpful for postponing decision making and bringing more economical conflict resolutions. Finally, case studies are made to show the application of multilevel conflict analysis model and some interesting findings are obtained. Specifically, once the cost of increasing analysis levels is taken into consideration, it is interesting to choose the optimal analysis level for making the most economic decision. The main contribution of this study is the model of multilevel conflict analysis based on fuzzy concept lattices, which can incorporate the uncertainties of two sides.

New Classification Method for Independent Data Sources Using Pawlak Conflict Model and Decision Trees.

The research concerns data collected in independent sets-more specifically, in local decision tables. A possible approach to managing these data is to build local classifiers based on each table individually. In the literature, many approaches toward combining the final prediction results of independent classifiers can be found, but insufficient efforts have been made on the study of tables' cooperation and coalitions' formation. The importance of such an approach was expected on two levels. First, the impact on the quality of classification-the ability to build combined classifiers for coalitions of tables should allow for the learning of more generalized concepts. In turn, this should have an impact on the quality of classification of new objects. Second, combining tables into coalitions will result in reduced computational complexity-a reduced number of classifiers will be built. The paper proposes a new method for creating coalitions of local tables and generating an aggregated classifier for each coalition. Coalitions are generated by determining certain characteristics of attribute values occurring in local tables and applying the Pawlak conflict analysis model. In the study, the classification and regression trees with Gini index are built based on the aggregated table for one coalition. The system bears a hierarchical structure, as in the next stage the decisions generated by the classifiers for coalitions are aggregated using majority voting. The classification quality of the proposed system was compared with an approach that does not use local data cooperation and coalition creation. The structure of the system is parallel and decision trees are built independently for local tables. In the paper, it was shown that the proposed approach provides a significant improvement in classification quality and execution time. The Wilcoxon test confirmed that differences in accuracy rate of the results obtained for the proposed method and results obtained without coalitions are significant, with a p level = 0.005. The average accuracy rate values obtained for the proposed approach and the approach without coalitions are, respectively: 0.847 and 0.812; so the difference is quite large. Moreover, the algorithm implementing the proposed approach performed up to 21-times faster than the algorithm implementing the approach without using coalitions.

Analysing the impact of stakeholder relationships in the optimisation of biomass supply chains

Many policies have been rolled out to help biomass supply chains reach their greatest contribution to combat climate issues. However, policies are often undermined by the failure to capture the impact of policy on interactions among players in the supply chain. When players in the supply chain have different perspectives toward a given policy, it impacts the way they interact with one another. This was not considered in the existing literature. A conflict analysis approach is applied to evaluate the impact of the supply chain player's relationship on supply chain decisions. Conflict analysis can be incorporated to mathematically model the behaviours of each supply chain player towards specific proposals or policies. To illustrate the effectiveness of the proposed conflict analysis-embedded model, a case study on a biofuel supply chain based in Malaysia is analysed. In this study, players' reactions in the supply chain toward the three proposed government policies (transport subsidy, workforce reduction and production variation) are systematically modelled and used as an input for the supply chain optimisation. A comparison study is shown to benchmark the results obtained with and without conflict analysis. Based on the optimised results, the conflict analysis model called for a higher amount of empty fruit bunch (i.e., 2.7 times higher between empty fruit brunch sources and first layer storage) than the model without conflict analysis. The total cost associated with the supply chain also increased by 77% after relationships among players were considered (USD 4.5 million to USD 8.0 million). The higher cost and material from the model suggested that conflict reduces the effectiveness of material transfer by reducing the chances of successful trade within the supply chain. By foreseeing and considering the inefficiency of a supply chain in a model, policymakers can, therefore, possible to make more sound decisions. The proposed approach with these findings is crucial in notifying the policymakers of the true potential of their policy toward the supply chain.