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July 2004 - April 2017
Publications
Publications (167)
Wargame has emerged as a preferred instrument for simulating combat decision-making. This paper employs machine learning methodologies to predict the outcome of wargame matches. Initially, we conducted data preprocessing on 335 wargame match replays, extracting and generating features from both macro and micro perspectives, thereby capturing player...
Presently, intelligent games have emerged as a substantial research area. Nonetheless, the slow convergence of intelligent wargame training and the low success rates of agents against specific rules present challenges. In this paper, we propose a game confrontation algorithm combining the multiple attribute decision making (MADM) approach from mana...
In this paper, we propose a three-way decision (TWD) method on multi-scale single-valued neutrosophic decision systems (MS-SVNDSs). First, to explore the application of single-valued neutrosophic sets (SVNSs) in multi-scale environment, we establish a rough set model of MS-SVNDSs. Then, aiming at the problem of knowledge acquisition in MS-SVNDSs, w...
Deep reinforcement learning has proven to be effective in various video games, such as Atari games, StarCraft II, Google research football (GRF), and Dota II. We participated in the 2022 IEEE Conference on Games Football AI Competition and ranked in the top eight. Despite recent efforts, building agents for GRF still suffers from multi-agent coordi...
With the development of society, intelligent games have gradually become a hot research field. The paper proposes an algorithm that combines the multi-attribute decision-making and reinforcement learning methods to apply to multi-agents' decision-making for wargaming AI (artificial intelligence). This algorithm solves the problem of the agent's low...
Conflict analysis gives guidelines for conflict resolution, which has been thoroughly studied and received widespread interest. Three-way conflict analysis research has achieved remarkable results and has been extended to Pythagorean fuzzy information systems because the three-way decision coincides with three attitudes of agents on issues, where t...
Recently, vision transformers have achieved impressive success in computer vision tasks. Nevertheless, these models suffer from heavy computational cost for the quadratic complexity of the self-attention mechanism, especially when dealing with high-resolution images. Previous literature has illustrated the sparsity of attention, which suggests that...
In recent years, many scholars have explored a variety of methods integrating three-way decision (3WD) and multi-attribute decision making (MADM), which enables the classification and priority ranking of alternatives possible and fully reflects the effectiveness and advantages of 3WD in solving MADM problems. However, few of these methods can effec...
Due to the effectiveness and advantages of interval-valued intuitionistic fuzzy sets (IVIFSs) in evaluating uncertainty and risk, we introduce IVIFSs into loss functions of decision-theoretic rough sets (DTRSs) and propose an optimization-based approach to interval-valued intuitionistic fuzzy three-way decisions. First, based on the classical DTRSs...
The application of artificial intelligence (AI) in games has been significantly developed and attracted much attention over the past few years. This article not only leverages the reinforcement learning multiagent deep deterministic policy gradient algorithm to realize the dynamic decision-making of game AI but also creatively incorporates deep lea...
The reinforcement learning problem of complex action control in multiplayer online battlefield games has brought considerable interest in the deep learning field. This problem involves more complex states and action spaces than traditional confrontation games, making it difficult to search for any strategy with human-level performance. This paper p...
The method of determining probability thresholds of three-way decisions (3WDs) has always been the key of research, especially in the current environment with a large number of data and uncertainties. Among these problems, there will be correlation and similarity between them. In the light of these problems, the loss function with Probabilistic Lin...
Three-way decision provides a practical and updated research orientation to deal with decision problems. In this article, a new three-way decision model combined with Z-numbers and third-generation prospect theory is proposed. To construct the proposed model, Z-numbers are utilized to depict the decision information containing in the outcome matrix...
Dimensionality reduction (DR) has been widely used to deal with high-dimensional data, and plays an important role in alleviating the so-called "curse of dimensionality". In this paper, we propose a novel unsupervised DR method with applications to face recognition, i.e., Nonnegative Representation based Discriminant Projection (NRDP). Different wi...
Regression-based methods have been widely applied in face identification, which attempts to approximately represent a query sample as a linear combination of all training samples. Recently, a matrix regression model based on nuclear norm has been proposed and shown strong robustness to structural noises. However, it may ignore two important issues:...
Regression analysis based methods have shown strong robustness and achieved great success in face recognition. In these methods, convex
$l_1$
-norm and nuclear norm are usually utilized to approximate the
$l_0$
-norm and rank function. However, such convex relaxations may introduce a bias and lead to a suboptimal solution. In this paper, we pro...
Three-way decision provides a new perspective for dealing with uncertainty and complexity in decision-making problems. However, behaviors of decision-makers may be influenced by different risk attitudes in reality. To address this problem, we construct a regret-based three-way decision model under interval type-2 fuzzy environment. Basically, regre...
In three-way decision, how to reflect the risk attitude in determining decision rules is an important issue. In the classical three-way decision model, loss functions are used to measure risks and determine the minimum-cost decision rules. On this basis, the utility function has been used as a new risk measurement to determine the maximum-utility d...
In three-way decision, the description on the risk attitude of decision-makers is a focus topic. In this paper, we propose a novel three-way decision model based on cumulative prospect theory. First, with the aid of a reference point, the value functions are utilized to describe different risk appetites of decision-makers towards gains and losses....
In recent years, three-way decisions have received much attention in uncertain decision and cost-sensitive learning communities. However, in many real applications, labeled samples are usually far from sufficient. In this case, it is a reasonable choice to defer the decision rather than make an immediate decision without sufficient supported inform...
Autoencoder network is an efficient representation learning method. In general, a finer feature set obtained from autoencoder leads to a lower error rate and lower total misclassification cost. However, the network is usually trained for a long time to obtain a finer feature set, leading to a high time cost and total cost. To address this issue, a...
In agent evaluation, a specific role-playing may need more than one capabilities or the task execution process can be divided into several stages. The diverse perspectives to assess candidate agents are denoted as attributes, which is more practical than treating experts as attributes in many other works. In the evaluation table, the attribute valu...
In most previous cost-sensitive feature extraction methods, the image matrix needs to be converted into vectors. The conversion always leads to a high computation complexity and small sample size problem. To address these issues, we propose a matrix-feature extraction method for face recognition, Cost-sensitive Dual-Bidirectional Linear Discriminan...
Most traditional face recognition classifiers attempt to minimize recognition error rate rather than misclassification costs, which is unreasonable in many real world applications. On the other hand, many facial images are usually unlabeled, and the label process may result in high costs. Considering imbalanced misclassification costs and the hards...
Three-way decisions were originally derived from decision-theoretic rough sets (DTRSs). A fundamental and important problem on DTRSs operating in multiple environments is how to determine the threshold parameter pairs based on loss functions. In this paper, we establish a theoretic and systematic framework for the optimization of the threshold para...
Many existing intuitionistic fuzzy (IF)decision methods focus on a reasonable ranking for alternatives under unknown weight information. Traditionally, the weight information is usually determined from a multiobjective optimization model based on real-valued measures such as IF distance or similarity measures, which may lose divergence information....
Role negotiation is a pivotal step in the role-based collaboration (RBC) process. There are many factors to be considered when decision makers set up criteria to evaluate group performance and agents' abilities. In this paper, we investigate the applications of three traditional multicriteria decision making methods into role negotiation of RBC, i....
In the study of intuitionistic fuzzy clustering, the construction of an intuitionistic fuzzy similarity matrix (IFSM) is a fundamental and important issue in the direct clustering analysis, since it determines clustering results and computational efforts. Many methods based on the axioms of intuitionistic fuzzy similarity relations are applicable t...
From an optimization point of view, we propose a new method to determine the loss funtion of intuitionistic fuzzy three-way decisions. First, two linear programming models are constructed to determine a pair of thresholds in three-way decisions based on their practical semantics. Meanwhile, the validity of the models is verified by KKT conditions....
Sequential three-way decisions approach has been demonstrated as an effective methodology of human problem solving with the aid of multiple levels of granularity. Searching an appropriate information granularity for decision or classification is a crucial issue. In this paper, inspired by the principle of justifiable granularity, we investigate a n...
Multi-granulation rough sets (MGRSs) and decision-theoretic rough sets (DTRSs) are important and popular extended types of Pawlak's classical rough set model. Multi-granulation DTRSs (MG-DTRSs), which combine these two generalized rough set models, have been investigated in depth in recent years to handle noisy distributed data. However, this combi...
Cooperative communication has emerged to reap the benefits of spatial diversity. To fully exploit cooperative diversity, we propose a medium access control and routing enabled cross-layer cooperative transmission (MACR-CCT) protocol for improving the performance in multi-hop wireless ad hoc networks (MWAN). Different from previous cooperative proto...
The similarity degree and divergence degree between intuitionistic fuzzy objects are defined respectively, and the related properties are presented in this paper. Then, we define the \((\alpha ,\beta )\)-level cut-sets based on intuitionistic fuzzy similarity relation under decision objective circumstances. Moreover, the upper and lower approximati...
Three-way decision (3WD) models have been widely investigated in the fields of approximate reasoning and decision making. Recently, sequential 3WD models have attracted increasing interest, especially for image data analysis. It is essential to select an appropriate feature extraction and granulation method for sequential 3WD-based image data analy...
Cost is an important issue in real world data mining. In rough set community, test cost and decision cost are two popular costs which are addressed by many researchers. In recent years, these two costs have been widely discussed from the standpoint of attribute reduction. However, few works pay attention on the construction of cost-sensitive based...
In rough set model, α quantitative indiscernibility relation is a generalization of both strong and weak indiscernibility relations. However, such three indiscernibility relations based rough sets do not take the test costs of the attributes into consideration. To solve this problem, a test-cost-sensitive α quantitative indiscernibility relation ba...
Collaboration is complex. To solve a problem occurring in collaboration, using computers, we must first define and specify the problem. This paper presents a challenging problem in collaboration, called group role assignment with cooperation and conflict factors (GRACCFs). This problem's solution aims at creating a high-performance group by role as...
Recent years have witnessed the ever increasing renewable penetration in power generation systems, which entails modern unit commitment problems with modelling and computation burdens. This study aims to simulate the impacts of manifold uncertainties on system operation with emission concerns. First, probability theory and fuzzy set theory are appl...
Brooks’ law is popular in software development. It has been used as a reference for managing software projects for over four decades. However, not enough investigations express this law in a quantitative way that can provide specific project recommendations at critical times in the development process. This paper offers a quantitative way based on...
Exploring rough sets from the perspective of covering represents a promising direction in rough set theory, where concepts are approximated by substituting of an equivalent relation in classical rough set theory with a covering in covering-based rough set theory. By combining intuitionistic fuzzy (IF) β-neighborhoods induced by an IF β-covering wit...
The hierarchical structures and uncertainty measures in granular computing are the two main aspects for investigating the structure and uncertainty of all types of approximation spaces. Although several hierarchical structures and uncertainty measures have been proposed to represent and analyze different granular structures, these structures and un...
Attribute reduction is an important topic in Decision-Theoretic Rough Set theory. To overcome the limitations of lower-approximation-monotonicity based reduct and cost minimum based reduct, a moderate attribute reduction approach is proposed in this paper, which combines the lower approximation monotonicity criterion and cost minor criterion. Furth...
Recently, Deep Belief Networks (DBNs) have received much attention in speech recognition communities. However, there are rare methods to set the appropriate hidden layers of DBNs. In this paper, we study the relationship between the number of hidden layers and the invariant features of speech signals, and the time cost of the accuracy of speech rec...
Unit commitment, as one of the most important control processes in power systems, has been studied extensively in the past decades. Usually, the goal of unit commitment is to reduce as much production cost as possible while guaranteeing the power supply operated with a high reliability. However, system operators encounter increasing difficulties to...
Many previous studies on face recognition attempted to seek a precise classifier to achieve a low misclassification error, which is based on an assumption that all misclassification costs are the same. In many real-world scenarios, however, this assumption is not reasonable due to the imbalanced misclassification cost and insufficient high-quality...
In this study, we establish a bilevel electricity trading model where fuzzy set theory is applied to address future load uncertainty, system reliability as well as human imprecise knowledge. From the literature, there have been some studies focused on this bilevel problem while few of them consider future load uncertainty and unit commitment optimi...
How to integrate human (expert) into the procedure of decision-making is an important issue for the next generation of decision support systems (DSS). Based on the concepts related to humanware (Hw) in our research, including Hw, Hw technology, HW service, and Hw and knowledge, the framework of novel decision systems (NDS) is presented. Then this p...
Adaptive collaboration (AC) is essential for group performance optimization in collaborative systems. This paper begins by introducing AC within the context of solving a real-world problem. Next, AC problems are formalized based on the environment-class, agent, role, group, and object (E-CARGO) model. Three algorithms are proposed for solving AC pr...
Relay selection has been regarded as an effective method to improve the performance of cooperative communication system. However, frequent operation of relay selection can bring enormous control message overhead and thereby decrease the performance of cooperative communication. To reduce the relay selection frequency, in this paper, we propose a re...
Group role assignment with a flexible formation (GRAFF) is essential for group performance optimization in collaborative systems. In this paper, problems of GRAFF are formalized based on the Environment-Class, Agent, Role, Group, and Object (E-CARGO) model. Then, based on group role assignment (GRA) and linear programming (LP), two algorithms are p...
Exploring rough sets from the perspective of multigranulation represents a promising direction in rough set theory, where concepts are approximated by multiple granular structures represented by binary relations. Through a combination of multigranulation rough sets with intuitionistic fuzzy rough sets, this study develops a new multigranulation rou...
The number of web services on the Internet is increasing continuously. Determining a web service's domain is very helpful for many issues like web service discovery, composition and semantic annotation. Based on predefined domains, we implemented semi-automatic web service classification with supervised machine learning technique in the paper. Firs...
It is a key problem to schedule the multiple unmanned ground vehicles and to achieve reliable target handover in an area needs to be continuously monitored. This research is concerned with the coordinated relay tracking of a moving target. Two relay tracking strategies are proposed. We first present the definition of the relay tracking. Then a rela...
In this paper, an effective decision process method is proposed to address the challenge in a multiple criteria decision-making (MCDM) problem because of large number of criteria. This method is based on the criteria reduction, tolerance relation, and prospect theory (PT). By building a discernibility matrix for tolerance relation (DMTR) in an MCDM...
Web Service Composition (WSC) has been a hot research topic in the past decade because it can carry out complex tasks. The main methods to study WSC include workflow, process algebra and semantics. It's very possible that user's goal is not consistent with WSC's goal. For this, a new method of WSC based on BDI (Belief-Desire-Intention) has been pro...
Adaptive Collaboration (AC) is essential for group performance optimization in collaborative systems. This paper begins by introducing AC within the context of solving a real world problem. Next, AC problems are formalized based on the Environment-Class, Agent, Role, Group, and Object (E-CARGO) model. Three algorithms are then proposed for solving...
This research is concerned with coordinated standoff tracking, and a guidance law against a moving target is proposed by using differential geometry. We first present the geometry between the unmanned aircraft (UA) and the target to obtain the convergent solution of standoff tracking when the speed ratio of the UA to the target is larger than one....
Quality of service (QoS) model of composite services and web service selection based on QoS are currently the hot issues in the web service composition area. Service selection based on QoS, which is a globally optimal selection issue, is a NP-hard problem. Taking engine into consideration, this paper develops a QoS model for service selection in th...
Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers. A simplex decision model can not provide a full...
Three-way decision model is an extension of two-way decision model, in which boundary region decision is regarded as a new feasible decision choice when precise decision can not be immediately made due to lack of available information. In this paper, a cost-sensitive sequential three-way decision model is presented, which simulate a gradual decisio...
For most attribute reduction in Pawlak rough set model (PRS), monotonicity is a basic property for the quantitative measure of an attribute set. Based on the monotonicity, a series of attribute reductions in Pawlak rough set model such as positive-region-preserved reductions and condition entropy-preserved reductions are defined and the correspondi...
Wireless sensor and actuator networked control system(WSANCS) is composed of a group of distributed sensors and actuators that communicate through wireless link which achieves distributed sensing and executing tasks. The time delay of the controlled plant and wireless transmission may have bad impacts on the system performances. Aiming at solving t...
In this paper, we propose a new model for decision support to address the ‘large decision table’ (eg, many criteria) challenge in intuitionistic fuzzy sets (IFSs) multi-criteria decision-making (MCDM) problems. This new model involves risk preferences of decision makers (DMs) based on the prospect theory and criteria reduction. First, we build thre...
With increasing demands on software functions, software systems become more and more complex. This complexity is one of the most pervasive factors affecting software development productivity. Assessing the impact of software complexity on development productivity helps to provide effective strategies for development process and project management....
Currently, service-oriented architecture (SOA) is implemented by using web service technology. SOA-based decision support systems (DSS) can solve structured problems, but cannot solve semi-(un-)structured problems satisfactorily. To enhance the capability of SOA-based DSS, we present the innovative idea of “human as a service” and the concept of Hu...
In general, the DSS (Decision Support System) is constructed with Software Services, which can't solve abstract or nonlinear problems perfectly. Based on this, Human ware Service blending into traditional DSS provides a good path, upon that it forms of the novel DSS. In this paper, the focus is the conceptual service invocation framework in the nov...
In general, DSS (Decision Support System) is constructed with Software Services, which can't solve abstract or nonlinear problems perfectly. Based on this, Humanware Service blending into the traditional DSS provides a good path, upon that it forms of the novel DSS. In this paper, the focus is the conceptual service invocation framework in the nove...
QoS model of composite services and Web services selection based on QoS are currently the hot issues in the web service composition area. Services selection based on QoS, which is a global optimal selection issue, has been proved a NP-HARD problem. Takes engine into account, this paper builds the QoS model of service selection in the Web composite...
Dynamic deployment is one of the fundamental issues addressed in wireless sensor networks (WSNs). This paper proposes a virtual force-aided particle swarm optimization (VFAPSO) for the purpose of maximum coverage area in WSNs which consist of stationary and mobile sensor nodes. The proposed algorithm takes advantage of the virtual force (VF) and pa...
Traditional web service discovery methods usually calculate the matching degrees of user demands and available services one by one, which is time-costing and not suitable for the open, dynamic and large network environment. In this paper, an incremental semantic web service discovery method based on Formal Concept Analysis (FCA) is proposed. Furthe...