Browse Proceedings

In recent years, many warehouses applied mobile robots to move products from one location to another. We focus on a traditional warehouse where agents are humans and they are engaged with tasks to navigate to the next destination one after the ...

Current methods for authentication and key agreement based on public-key cryptography are vulnerable to quantum computing. We propose a novel approach based on artificial intelligence research in which communicating parties are viewed as ...

In the area of autonomous driving there is a need to flexibly configure and simulate more complex individual pedestrian behavior in critical traffic scenes which goes beyond predefined behavior simulation. This paper presents a novel human-...

Persuasive systems play a crucial role in supporting and counseling people to achieve individual behavior change goals. Intelligent systems have been used for inducing a positive adjustment of attitudes and routines in scenarios such as ...

There have been many attempts to integrate automated planning and rational agents. Most of the research focuses on adding support directly within agent programming languages, such as those based on the Belief-Desire-Intention model, rather than ...

Steam networks in existing chemical facilities are typically highly centralized and operate on long-term contracts. It results in energy systems with overcapacity of production, exceeding the demand several times. Facilities which remain idle or ...

Multi-agent techniques have become mature technologies with many tools, programming languages, and methodologies currently available. As a result, it is a practical approach for the development of complex AI systems. However, there are still ...

Coalitional games are models of cooperation where selfish agents must form groups (coalitions) to maximize their utility. In these models, it is generally assumed that the utility of a coalition is fixed and known. As these assumptions are not ...

Persuasion is an active research topic in artificial intelligence (AI), human-computer interaction (HCI), and social sciences. When persuasive technology has been designed, some HCI guidelines have commonly used disregarding the current AI state ...

Market-based task allocation mechanisms are designed to distribute a set of tasks fairly amongst a set of agents. Such mechanisms have been shown to be highly effective in simulation and when applied to multi-robot teams. Application of such ...

We have witnessed natural disasters in several regions. Although people focus on the events of tsunami, landslides in mountainous areas are serious issues to consider. Therefore, we have proposed a system that supports evacuation after the ...

Plastics and the pollution caused by their waste have always been a menace to both nature and humans. With the continual increase in plastic waste, the contamination due to plastic has stretched to the oceans. Many plastics are being drained into ...

This paper extends previous works on multi-agent-based simulation models of Coupled Human and Natural Systems (CHANS), by introducing a farmer agent model capable of interact with environmental, economic, and spatial variables in the context of ...

Traffic can be viewed as a complex adaptive system in which systemic patterns arise as emergent phenomena. Global behaviour is a result of behavioural patterns of a large set of individual travellers. However, available traffic simulation models ...

Recent innovations in Deep Reinforcement Learning (DRL) and Artificial Intelligence (AI) techniques have allowed for the development of artificial agents that can outperform human counterparts. But when it comes to multiagent task contexts, the ...

Autonomous agents may be required to form an understanding of other agents for which they don’t possess a model. In such cases, they must rely on their previously gathered knowledge of agents, and ground the observed behaviors in the models this ...

As the number of IoT applications increases, IoT devices are becoming more and more ubiquitous. Therefore, they need to adapt their functionality in response to the uncertainties of their environment to achieve their goals. In Human-centered IoT, ...

The worldwide COVID-19 pandemic has had a tremendous impact on the aviation industry, with a reduction in passenger demand never seen before. To minimize the spread of the virus and to gain trust from the public in the airport operations’ safety, ...

Agent-based simulation tools have found many applications in the field of Power and Energy Systems, as they can model and analyze the complex synergies of dynamic and continuously evolving systems. While some studies have been done w.r.t. ...

Robot swarms hold great potential for accomplishing missions in a robust, scalable, and flexible manner. However, determining what low-level agent behavior to implement in order to meet high-level objectives is an unsolved inverse problem. ...

Pricing decisions are increasingly made by AI. Thanks to their ability to train with live market data while making decisions on the fly, deep reinforcement learning algorithms are especially effective in taking such pricing decisions. In e-...

The paper dwells on solution to the problem of planning large-scale space observation systems, which can include from several dozens to hundreds of small spacecrafts. These systems are created in response to massive increase in the load on ...

Even before the ongoing recent deployment of 5G technology, Mobile Edge Computing was already considered as a key driver towards the development of vehicular use cases having stringent latency and bandwidth requirements. This paper relies on 5G ...

Multi-agent systems (MAS) are increasingly used in critical applications. To ensure dependability of MAS, we need to formally specify and verify their fault tolerance, i.e., to ensure that collaborative agent activities are performed correctly ...

Existing agent-based models of emotion contagion that account for the emotional diversity in groups have mostly focussed on the spread of categorical emotions (happy, sad, angry). In practice this raises problems with regard to how the spread of ...

We present a knowledge-driven multilingual conversational agent (referred to as “MyWelcome Agent”) that acts as personal assistant for migrants in the contexts of their reception and integration. In order to also account for tasks that go beyond ...

Many scientific datasets are generated in a given data structure (e.g., a graph) and are reused for various analyses. From this viewpoint, instead of streaming these datasets into conventional big-data tools such as MapReduce or Spark, we should ...

Current models for multi-agent organizations offer effective abstractions to build distributed systems, but lack a systematic way to address exceptions. This demonstration presents an exception handling mechanism in the context of the JaCaMo ...