Jialong Li

• Research Associate
• Professor (Assistant) at Waseda University

Human-robot collaboration has become increasingly complex and dynamic, highlighting the need for effective and intuitive communication. Two communication strategies for robots have been explored: (i) global-perspective strategy to share an overview of task progress, aimed at achieving consensus on completed and upcoming tasks; and (ii) local-perspe...

Multi-agent path finding (MAPF) is a safety-critical scenario where the goal is to secure collision-free trajectories from initial to desired locations. However, due to system complexity and uncertainty, integrating learning-based controllers with MAPF is challenging and cannot theoretically guarantee the safety of the learned controllers. In respo...

Multimodal interaction technology has become a key aspect of remote education by enriching student engagement and learning results as it utilizes the speech, gesture, and visual feedback as various sensory channels. This publication reflects on the latest breakthroughs in multimodal interaction and its usage in remote learning environments, includi...

In the evolution of software systems, especially in domains like autonomous vehicles, dynamic user preferences are critical yet challenging to accommodate. Existing methods often misrepresent these preferences, either by overlooking their dynamism or overburdening users as humans often find it challenging to express their objectives mathematically....

With advances in digital transformation (DX) in education and digital technologies becoming more deeply integrated into educational settings, global demand for video-based learning materials continues to rise, resulting in substantial effort being required from teachers to create e-learning videos. Furthermore, while many existing services offer vi...

With the rapid advancement of mobile technology, e-learning has expanded significantly, making language learning more accessible than ever. At the same time, the rise of artificial intelligence (AI) technologies has opened new avenues for adaptive and personalized e-learning experiences. However, traditional e-learning methods remain limited by the...

Social media platforms frequently impose restrictive policies to moderate user content, prompting the emergence of creative evasion language strategies. This paper presents a multi-agent framework based on Large Language Models (LLMs) to simulate the iterative evolution of language strategies under regulatory constraints. In this framework, partici...

External human-machine interfaces (eHMIs) are expected to improve pedestrian interactions with automated vehicles (AVs) and foster greater social acceptance. While earlier research has primarily focused on refining eHMI designs by examining different modalities and color preferences, determining the most effective eHMI location on vehicles remains...

Advancements in large language models (LLMs) have enhanced their ability to handle ambiguous user instructions. However, effective prompt patterns remain crucial for usability and comprehension. This article presents a taxonomy of prompt engineering patterns for software engineering. It is based on a systematic literature review that was conducted...

In self-adaptive software systems, the role of context is paramount, especially for proactive self-adaptation. Current research, however, does not fully explore context’s impact, for example on priorities of the requirements. To address this gap, we introduce a novel contextual goal model to capture these factors and their influence on the system....

In the studies of self-adaptive systems (SAS), requirement relaxation is a well-studied approach to adjust or disable certain requirements in response to requirement unsatisfaction or requirement conflicts, allowing the system to maintain core functionalities while temporarily reducing service quality. The recent integration of Guaranteeable Requir...

Self-adaptive systems (SASs) are designed to handle changes and uncertainties through a feedback loop with four core functionalities: monitoring, analyzing, planning, and execution. Recently, generative artificial intelligence (GenAI), especially the area of large language models, has shown impressive performance in data comprehension and logical r...

Diffusion models, which leverage stochastic processes to capture complex data distributions effectively, have shown their performance as generative models, achieving notable success in image-related tasks through iterative denoising processes. Recently, diffusion models have been further applied and show their strong abilities in planning tasks, le...

People with color vision deficiency often face challenges in distinguishing colors such as red and green, which can complicate daily tasks and require the use of assistive tools or environmental adjustments. Current support tools mainly focus on presentation-based aids, like the color vision modes found in iPhone accessibility settings. However, of...

Rule-based adaptation is a foundational approach to self-adaptation, characterized by its human readability and rapid response. However, building high-performance and robust adaptation rules is often a challenge because it essentially involves searching the optimal design in a complex (variables) space. In response, this paper attempt to employ lar...

Social recommendations typically utilize social relationships and past behaviors to predict users’ preferences. In real-world scenarios, the connections between users and items often extend beyond simple pairwise relationships. Leveraging hypergraphs to capture high-order relationships provides a novel perspective to social recommendation. However,...

Security attacks present unique challenges to the design of self-adaptation mechanism for software-intensive systems due to the adversarial nature of the environment. Game-theoretical approaches have been explored in security to model malicious behaviors and design reliable defense for the system in a mathematically grounded manner. However, modeli...

The Value Iteration Network (VIN) is a neural network widely used in path-finding reinforcement learning problems. The planning module in VIN enables the network to understand the nature of a problem, thus giving the network an impressive generalization ability. However, reinforcement learning (RL) with VIN can not guarantee efficient training due...

In this paper, we address the challenges faced by Value Iteration Networks (VIN) in handling larger input maps and mitigating the impact of accumulated errors caused by increased iterations. We propose a novel approach, Value Iteration Networks with Gated Summarization Module (GS-VIN), which incorporates two main improvements: (1) employing an Adap...

Modern systems suffer system faults in both hardware and software. Requirement degradation is a widely applied redundant-design approach to deal with system fault by degrading or disabling (non-critical) requirements. However, due to the environment's unpredictability, it is unrealistic for engineers to prepare such redundant designs for unforeseen...

In this paper, we address the challenges faced by Value Iteration Networks (VIN) in handling larger input maps and mitigating the impact of accumulated errors caused by increased iterations. We propose a novel approach, Value Iteration Networks with Gated Summarization Module (GS-VIN), which incorporates two main improvements: (1) employing an Adap...

In automated planning, a plan is synthesized to achieve the given goals in the assumed operational environment. However, during the plan’s execution, the operational environment may changes so that replanning a new plan is necessary against the changing environment. In some situations, it is impossible to achieve some goals anyhow; in other situati...

A self-learning adaptive system (SLAS) uses machine learning to enable and enhance its adaptability. Such systems are expected to perform well in dynamic situations. For learning high-performance adaptation policy, some assumptions must be made on the environment-system dynamics when information about the real situation is incomplete. However, thes...

“Human-hydroponics coexistence” is becoming a real scenario for indoor gardening and artificial ecological systems. Existing industry-use studies have focused on hydroponic cultivation under the assumption of a stable environment and no human interference. Thus, these studies are not suitable for “human-hydroponics coexistence” because “environment...

In event-based systems, safety properties are critical requirements to prevent the system from bad things happen. However, safety properties may be violated because of the runtime system functional fault. From the viewpoint of a self-adaptive system, such a system should be requirement-aware and changes its behavior to satisfy the designed requirem...

自己適応システムは，外部環境の変化に対し，システム自身が振る舞いを変更するシステムである．制御器合成技術[1]を利用した自己適応システムにおいて，システムは(1)変化した環境を検知し，(2)開発者が想定した要求から開発者の意図に沿って最大限に要求を保証する要求の集合を分析し，(3)分析された要求集合を保証するように振る舞いを変更する．相澤ら[2]は，ゲーム空間と勝利領域を構築し，保証できる最大限な要求集合を分析する手法と環境変化時の要求緩和分析手法を提案した．しかし，環境から望ましくない動作（開発者が想定してない外部環境から観測された動作）が発生しなくなる場合に，システムはより高いレベルの要求を保証可能(以下，requirementenhancementという)かどうかを分析するには数分間以...