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While Agent-Based Models can create detailed artificial societies based on individual differences and local context, they can be computationally intensive. Modelers may offset these costs through a parsimonious use of the model, for example…
Safe navigation of autonomous agents in human centric environments requires the ability to understand and predict motion of neighboring pedestrians. However, predicting pedestrian intent is a complex problem. Pedestrian motion is governed…
Social sensing services use humans as sensor carriers, sensor operators and sensors themselves in order to provide situation-awareness to applications. This promises to provide a multitude of benefits to the users, for example in the…
Untile recently crowdsourcing has been primarily conceived as an online activity to harness resources for problem solving. However the emergence of opportunistic networking (ON) has opened up crowdsourcing to the spatial domain. In this…
Perceiving the surrounding environment in terms of objects is useful for any general purpose intelligent agent. In this paper, we investigate a fundamental mechanism making object perception possible, namely the identification of…
Emotional cues frequently arise and shape group dynamics in interactive settings where multiple humans and artificial agents communicate through shared digital channels. While artificial agents lack intrinsic emotional states, they can…
An unaddressed challenge in multi-agent coordination is to enable AI agents to exploit the semantic relationships between the features of actions and the features of observations. Humans take advantage of these relationships in highly…
Social identities play an important role in the dynamics of human societies, and it can be argued that some sense of identification with a larger cause or idea plays a critical role in making humans act responsibly. Often social activists…
In this paper, we propose the problem of collaborative perception, where robots can combine their local observations with those of neighboring agents in a learnable way to improve accuracy on a perception task. Unlike existing work in…
Topic modeling of streaming sensor data can be used for high level perception of the environment by a mobile robot. In this paper we compare various Gibbs sampling strategies for topic modeling of streaming spatiotemporal data, such as…
Over the recent twenty years, argumentation has received considerable attention in the fields of knowledge representation, reasoning, and multi-agent systems. However, argumentation in dynamic multi-agent systems encounters the problem of…
With the advances in sensors and computer networks an increased number of Mixed Reality (MR) applications require large amounts of information from the real world. Such information is collected through sensors (e.g. position and orientation…
The context-awareness of things that belong to IoT networks have to be considered in a distributed computation paradigm. In the paper we suggest the use of graph transformations and temporal logic as a formal framework for a knowledge…
The rise of AI conversational agents has broadened opportunities to enhance human capabilities across various domains. As these agents become more prevalent, it is crucial to investigate the impact of different affective abilities on their…
Crowdsourced mobile video streaming enables nearby mobile video users to aggregate network resources to improve their video streaming performances. However, users are often selfish and may not be willing to cooperate without proper…
As automation and mobile robotics reshape work environments, rising expectations for productivity increase cognitive demands on human operators, leading to potential stress and cognitive overload. Accurately assessing an operator's mental…
Behavior prediction models have proliferated in recent years, especially in the popular real-world robotics application of autonomous driving, where representing the distribution over possible futures of moving agents is essential for safe…
Building Management Systems (BMSs) have evolved in recent years, in ways that require changes to existing network architectures that follow the store-then-analyse approach. The primary cause is the increasing deployment of a diverse range…
With the rapid growth of intelligent services, communication targets are shifting from humans to artificial intelligent (AI) agents, which require new paradigms to enable real-time perception, decision-making, and collaboration. Semantic…
Recently, there has been an emergence of employing LLM-powered agents as believable human proxies, based on their remarkable decision-making capability. However, existing studies mainly focus on simulating human dialogue. Human non-verbal…