Rapport with Virtual Agents: What do Human Social Cues and Personality Explain?

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Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...

In this paper, we propose a novel approach that employs kinetic equations to describe the collective dynamics emerging from graph-mediated pairwise interactions in multi-agent systems. We formally show that for large graphs and specific classes of interact ...

Reinforcement learning (RL) has shown promising results for real-time control systems, including the domain of plasma magnetic control. However, there are still significant drawbacks compared to traditional feedback control approaches for magnetic confinem ...

Large language models (LLMs) have shown strong performance in tasks across domains but struggle with chemistry-related problems. These models also lack access to external knowledge sources, limiting their usefulness in scientific applications. We introduce ...

EncodingActs investigates how computational methods can facilitate the transmission of multifaceted knowledge within intangible cultural heritage (ICH). ICH, characterized by living, tacit, yet complex epistemic systems, is conventionally viewed as challen ...

Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

As the field of ethology advances, especially over the past two decades, the role of animal-robot interaction tools has increasingly become essential. This importance arises from the need for controlled, repetitive, repeatable, and long-duration experiment ...

This paper considers the problem of resilient distributed optimization and stochastic learning in a server-based architecture. The system comprises a server and multiple agents, where each agent has its own local cost function. The agents collaborate with ...

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

Background: Cannabis use and cannabis use disorder (CUD) are associated with mental health disorders, however the extent of this matter among pregnant and recently postpartum (e.g., new moms) women in the US is un-known. Associations between cannabis use, ...

This article reviews significant advances in networked signal and information processing (SIP), which have enabled in the last 25 years extending decision making and inference, optimization, control, and learning to the increasingly ubiquitous environments ...

Language has shaped human evolution and led to the desire to endow machines with language abilities. Recent advancements in natural language processing enable us to achieve this breakthrough in human-machine interaction. However, introducing conversational ...

In multi-agent reinforcement learning, multiple agents learn simultaneously while interacting with a common environment and each other. Since the agents adapt their policies during learning, not only the behavior of a single agent becomes non-stationary, b ...

The collective behavior of animals has been traditionally studied through observation, quantitative models of behavior, and devices of low intelligence. Nowadays, the advancements in the field of robotics allow for closed-loop experiments that occur in rea ...

Robotics and neuroscience are sister disciplines that both aim to understand how agile, efficient, and robust locomotion can be achieved in autonomous agents. Robotics has already benefitted from neuromechanical principles discovered by investigating anima ...

The adaptive social learning paradigm helps model how networked agents are able to form opinions on a state of nature and track its drifts in a changing environment. In this framework, the agents repeatedly update their beliefs based on private observation ...

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

Adolescent individuals exhibit great variability in cortical dynamics and behavioral outcomes. The developing adolescent brain is highly sensitive to social experiences and environmental insults, influencing how personality traits emerge. A distinct patter ...

This work addresses the problem of sharing partial information within social learning strategies. In social learning, agents solve a distributed multiple hypothesis testing problem by performing two operations at each instant: first, agents incorporate inf ...

In this article, we study the problem of Byzantine fault-tolerance in a federated optimization setting, where there is a group of agents communicating with a centralized coordinator. We allow up to

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Byzantine-faulty agents, which may not follow a prescr ...

Rapport with Virtual Agents: What do Human Social Cues and Personality Explain?

Chattez avec Graph Search

Stochastic pairwise preference convergence in Bayesian agents

Network-based kinetic models: Emergence of a statistical description of the graph topology

Towards practical reinforcement learning for tokamak magnetic control

Augmenting large language models with chemistry tools

EncodingActs: Modeling, Representing and Transmitting Embodied Knowledge in Traditional Martial Arts

Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

Challenges and approaches in bridging the biomimicry gap in biohybrid systems of fish and robots

Impact of Redundancy on Resilience in Distributed Optimization and Learning

Multi-agent Learning with Privacy Guarantees

Cannabis use, cannabis use disorder and mental health disorders among pregnant and postpartum women in the US: A nationally representative study

Networked Signal and Information Processing: Learning by multiagent systems

Towards Novel Evaluation Methods for Social Dialog Systems

Multi-agent actor-critic with time dynamical opponent model

A biohybrid interaction framework for the integration of robots in animal societies

The neuromechanics of animal locomotion: From biology to robotics and back

Discovering Influencers in Opinion Formation Over Social Graphs

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Transcriptomic analysis reveals mitochondrial pathways associated with distinct adolescent behavioral phenotypes and stress response

Partial Information Sharing Over Social Learning Networks

Byzantine Fault-Tolerance in Federated Local SGD Under 2f-Redundancy