Yuan Yao

McGill University | McGill · School of Computer Science

This paper proposes a novel learning algorithm for a self-constructing fuzzy neural network (SCFFN) design. The network is built based on ellipsoidal basis function (EBF), which can be divided into two parts. The first hidden layer composed of EBF units is considered as IF-part, and the output layer which consists of the connect weights is the THEN...

As a complex nonlinear system, greenhouse can not be controlled perfectly by traditional control strategies. This paper proposes a self-organizing fuzzy neural network controller (SOFNNC) with group-based genetic algorithm (GGA) to drive the internal climate of the greenhouse. SOFFNNC is a hybrid control strategy which combines fuzzy control and ne...

Now, autonomous tasks planning and allocating (TPA) in Multi Agent System (MAS) has been one key and fundamental problem to promote the intelligent level of such system. Autonomous TPA means that, all tasks should be (re)planned and (re)allocated automatically according to the synthesis constraints and the dynamic environment aspects, such as the c...

This paper proposes an approach to implement TSK model by using a self-constructing fuzzy neural network (SCFNN). This network is built based on ellipsoidal basis function (EBF), which can be divided into two parts. The first hidden layer composed of EBF units is considered as IF-part, and the output layer which consists of the connect weights is t...

This paper proposes a novel parameter learning algorithm for a self-constructing fuzzy neural network (SCFFN) design. It concludes dynamic prior adjustment (DPA) which is employed to adjust parameters according to the distribution of the input samples and group-based symbiotic evolution (GSE) which is applied to train all the free parameters for th...

The existing deep reinforced learning algorithms cannot see local environments and have insufficient perceptual information on UAV autonomous navigation tasks. The paper investigates the UAV's autonomous navigation tasks in its unknown environments based on the nondeterministic policy soft actor-critic (SAC) reinforced learning model. Specifically,...

UAVs need to use a large number of sensors to complete autonomous navigation tasks in indoor environments. The evaluation of multi-sensors ranging capabilities in different application scenarios is an important research direction at present. This paper analyzes three main factors (light intensity, distance, target material) affecting the ranging ca...

Multi-agent deep reinforcement learning (MDRL) has attracted attention for solving complex tasks. Two main challenges of MDRL are non-stationarity and partial observability from the perspective of agents, impacting the performance of agents’ learning cooperative policies. In this study, Controlled and Targeted Communication with the Centralized Cri...

Centralized training and decentralized execution have become a basic setting for multi-agent reinforcement learning. As the number of agents increases, the performance of the actors that only use their own local observations with centralized critics is prone to bottlenecks in complex scenarios. Recent research has shown that agents learn when to co...

New generation airborne embedded system has deployed Graphical Processing Units (GPUs) to raise processing capability to meet growing computational demands. Comparing with the cloud system, the airborne embedded system usually has a fixed application set, but strict real-time constraints. Unfortunately, the inherent GPU scheduler does not consider...

Deep learning has recently been shown to provide great achievement to the traveling salesman problem (TSP) on the Euclidean graphs. These methods usually fully represent the graph by a set of coordinates, and then captures graph information from the coordinates to generate the solution. The TSP on arbitrary symmetric graphs models more realistic ap...

With the proliferation of increasingly powerful mobile devices and wireless networks, mobile crowdsourcing has emerged as a novel service paradigm. It enables crowd workers to take over outsourced location-dependent tasks, and has attracted much attention from both research communities and industries. In this paper, we consider a mobile crowdsourci...

Route planning is considered as one of the fundamental technologies in the navigation system, which finds an optimal route between a pair of source and target locations. Navigation services are required to provide real-time responses to route planning queries to promote user experiences on the road under different situations, such as sudden detour,...

This paper proposes a learning-based approach to optimize the multiple traveling salesman problem (MTSP), which is one classic representative of cooperative combinatorial optimization problems. The MTSP is interesting to study, because the problem arises from numerous practical applications and efficient approaches to optimize the MTSP can potentia...

The inter-vehicle safety communication is generally considered as a promising technology to significantly enhance road safety. In fact, a lot of communications about inter-vehicle safety have real-time, rigorous requirements on broadcast messages in order to make sure that drivers have sufficient time for reaction towards emergencies. The procedure...

Motion planning is a crucial topic with multi-UAV applications of search and rescue missions, transportation missions, etc. The concerns of motion planning focus on path planning and inter-UAV collision avoidance. Model based on Lyapunov present great solutions. However, setting reasonable parameters for the model is usually based on experience. Mo...

With the development of unmanned systems, the scale and application scenarios of unmanned swarms have greatly expanded. At present, the research on swarms mainly focuses on the swarm intelligent bionic strategy and the implementation of obstacle avoidance algorithms for specific task scenarios. In the process of swarm control, due to the complex na...

Vehicular Ad Hoc Networks (VANETs) have far-reaching application potentials in the Intelligent Transportation System (ITS) such as traffic management, accident avoidance and in-car infotainment. However, security has always been a challenge to VANETs, which may cause severe harm to the ITS. Sybil attack is considered as a serious security threat to...

Information about urban safety, e.g., the safety index of a position, is of great importance to protect humans and support safe walking route planning. Despite some research on urban safety analysis, the accuracy and granularity of safety index inference are both very limited. The problem of analyzing urban safety to predict safety index throughout...

Most of commercial navigation products provide route planning service for users. However, they only consider a single metric such as distance, time or other costs, while ignoring a critical criterion: safety. In a smart city, people may prefer to find a safe walking route to avoid the potential crime risk as well as obtain a short distance. This pr...

Network-based malware has posed serious threats to the security of host machines. When malware adopts a private TCP/IP stack for communications, personal and network firewalls may fail to identify the malicious traffic. Current firewall policies do not have a convenient update mechanism, which makes the malicious traffic detection difficult. In thi...

Vehicular Ad Hoc Networks (VANETs) bring many benefits and conveniences to road safety and drive comfort in future transportation systems. Sybil attack is one of the most risky threats since it violates the fundamental assumption of VANETs-based applications that all received information are correct and trusted. Sybil attacker can generate multiple...

IEEE 802.11p/1609.4 standard supports both safety applications and non-safety services for Vehicular Ad Hoc Networks (VANETs) via multi-channel operations. In this letter, we establish an analytical model to calculate the optimal bandwidth resource allocation and propose a Flexible Multi-channel Coordination MAC (FMC-MAC) protocol for VANETs. The F...

The existing study shows that safety applications supported by vehicle-to-vehicle (V2V) communications have the potential to address 80% of all road crash issues. IEEE 802.11p is a key enabling technology to support V2V safety applications. To meet the stringent delay and reliability requirements of these applications, rate adaptation (RA) approach...

Automobile manufacturers are delivering a new generation of connected vehicles with in-cabin Wi-Fi devices, enabling advances in a wide range of in-vehicle communications and infotainment capabilities. The communication performance is a key factor enabling the instant multimedia streaming. A fundamental question remains to be explored: as every run...

In this letter, we propose a density-aware rate adaptation (DARA) protocol to ensure reliable vehicle safety communication in a highway broadcast environment. DARA significantly improves system reliability by addressing the challenges of estimating channel conditions caused by various dynamics due to factors, including channel fading, interference,...

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications are gaining increasing importance in vehicular applications. Dedicated short-range communication (DSRC) is a fundamental set of short-to-medium-range communication channels and a set of protocols and standards that are specifically designed for V2V and V2I communications. I...

As a key enabling technology for the next generation inter-vehicle safety communications, The IEEE 802.11p protocol is currently attracting much attention. Many inter-vehicle safety communications have stringent real-time requirements on broadcast messages to ensure drivers have enough reaction time toward emergencies. Most existing studies only fo...

Robot, spaceship and other applications that can be called autonomous Cyber-Physical Systems (CPS) are all smart embedded systems, which usually run in open environment by themselves with inhered intelligent capabilities. Besides the application intelligence, the researches of adaptive platform for such systems have also become topics recently. Bas...

According to the environment adaptability requirement of an autonomous agent system, this paper studies the mapping relationships between the dynamic environment aspects and task scheduling, and then, gives the definitions and computation models of the task, quality of scheduling (QoS) and fitness. Considering the dynamic and inaccurate parameters...