Unmanned Aerial Vehicles (UAVs) are necessary across diverse domains, including disaster surveillance and wildlife conservation. However, the development and evaluation of UAV-related algorithms often encounter a significant hurdle: the scarcity of ...

In the domain of video generation, Text-to-video suffers from a notable application gap due to lack of audio that harmonizes with the visual content. Current solutions typically dubbing based solely on the original text used for generate video, which ...

Multimodal Question Answering (MMQA) is crucial as it enables comprehensive understanding and accurate responses by integrating insights from diverse data representations such as tables, charts, and text. Most existing researches in MMQA only focus on ...

Theory of Mind (ToM) is a capability of humans to attribute mental states to other agents allowing us to reason on the agent’s intentions and predict their future behavior. The complexity of ToM paves a way for an open arena of development for ...

This research builds a realtime and multi-agent system to handle Distributed Denial of Service (DDoS) attacks. The integration of an Intrusion Detection System (IDS), Security Information and Event Management (SIEM), and Security Orchestration, ...

Cooperative adaptive cruise control (CACC) is a smart transportation solution to alleviate traffic congestion and enhance road safety. The performance of CACC systems can be remarkably affected by communication time delays, and traditional control methods ...

Deep or reinforcement learning (RL) approaches have been adapted as reactive agents to quickly learn and respond with new investment strategies for portfolio management under the highly turbulent financial market environments in recent years. In many ...

Learning in general-sum games often yields collectively sub-optimal results. Addressing this, opponent shaping (OS) methods actively guide the learning processes of other agents, empirically leading to improved individual and group performances. Early OS ...

Aiming at the problem of aggravation of traffic congestion caused by unstable signal control of traffic signal control system, the Multi-Agent Deep Deterministic Policy Gradient-based Traffic Cyclic Signal (MADDPG-TCS) control algorithm is used to ...

The swift evolution of the internet has delivered convenience to people while also introducing challenges concerning the security of information. Network intrusion detection, which recognises distinct attack behaviours in the network by gathering and ...

Recent advances in learning reusable motion priors have demonstrated their effectiveness in generating naturalistic behaviors. In this paper, we propose a new learning framework in this paradigm for controlling physics-based characters with improved ...

Homogeneous Multi-Agent Reinforcement Learning (MARL) is well studied in games, robots, and simulations. What has not been fully explored is the effectiveness of Heterogeneous MARL in the building space. Heterogeneous MARL has been proven to be more ...

Over the past years, augmented reality (AR) based on mobile phones has gained great attention. When multiple phones are used in AR applications, collaborative simultaneous localization and mapping (SLAM) is considered one of the enabling technologies, ...

As mobile communication technologies advance, mobile networks become increasingly complex, and user requirements become increasingly diverse. To satisfy the diverse demands of users while improving the overall performance of the network system, the ...

Explaining the decision-making policies of deep reinforcement learning is challenging owing to the black-box nature of neural networks. We address this challenge by combining deep learning models and symbolic structures into a neural-logic model ...

Autonomous decision making for cyber-defence in operational situations is desirable but challenging. This is due to the nature of operational technology (because of its cyber-physical nature) as well as the need to account for multiple contexts. ...

Traditional multi-path routing methods distribute evenly traffic across multiple paths in a network, which can lead to inefficient use of resources if some paths are significantly longer or less reliable than others. Weighted multi-path routing ...

In this paper, we investigate that swarm multi-agent can trap multi-target and avoid obstacles simultaneously through cooperative control. First, the control method proposed in this paper allows the number of multi-agent to trap each target evenly,...

Human supervision of multiple fielded robots is a challenging task which requires a thoughtful design and implementation of both the underlying infrastructure and the human interface. It also requires a skilled human able to manage the workload and ...

Agent based modeling (ABM) is a computational approach to modeling complex systems by specifying the behavior of autonomous decision-making components or agents in the system and allowing the system dynamics to emerge from their interactions. Recent ...