Concept

Embodied agent

Related publications (122)

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Opinion Formation over Adaptive Networks

Virginia Bordignon

An adaptive network consists of multiple communicating agents, equipped with sensing and learning abilities that allow them to extract meaningful information from measurements. The objective of the network is to solve a global inference problem in a decent ...

EPFL2022

Scalable Multi-agent Coordination and Resource Sharing

Panayiotis Danassis

A plethora of real world problems consist of a number of agents that interact, learn, cooperate, coordinate, and compete with others in ever more complex environments. Examples include autonomous vehicles, robotic agents, intelligent infrastructure, IoT de ...

EPFL2022

Exploiting environmental signals to enable policy correlation in large-scale decentralized systems

Boi Faltings, Zeki Doruk Erden, Panayiotis Danassis

Can artificial agents benefit from human conventions? Human societies manage to successfully self-organize and resolve the tragedy of the commons in common-pool resources, in spite of the bleak prediction of non-cooperative game theory. On top of that, rea ...

SPRINGER2022

Improved Cooperation by Exploiting a Common Signal

Boi Faltings, Zeki Doruk Erden, Panayiotis Danassis

International Foundation for Autonomous Agents and Multiagent Systems2022

Children, Robots, and Virtual Agents: Present and Future Challenges

Shruti Chandra, Elmira Yadollahi

Research on child-agent interaction is rapidly expanding. It is, therefore, necessary to converge our collective efforts to broaden our understanding and perspectives of how virtual agents, affect and potentially improve the well-being of children. "Childr ...

ASSOC COMPUTING MACHINERY2021

Ageing and reinforcement learning

Michael Herzog, Wei-Hsiang Lin

Learning to achieve one’s goal in a complex environment is a complicated task. In reinforcement learning (RL) tasks, an agent interacts with the environment to learn optimal actions. In humans, striatal areas are strongly involved in these tasks. During ag ...

2021

Orthos: A Trustworthy AI Framework for Data Acquisition

Boi Faltings, Sujit Prakash Gujar, Dimitrios Chatzopoulos

Information acquisition through crowdsensing with mobile agents is a popular way to collect data, especially in the context of smart cities where the deployment of dedicated data collectors is expensive and ineffective. It requires efficient information el ...

Springer2021

Social Learning Under Inferential Attacks

Ali H. Sayed, Stefan Vlaski, Virginia Bordignon, Konstantinos Ntemos

A common assumption in the social learning literature is that agents exchange information in an unselfish manner. In this work, we consider the scenario where a subset of agents aims at driving the network beliefs to the wrong hypothesis. The adversaries a ...

IEEE2021

Towards versatile conversations with data-driven dialog management and its integration in commercial platforms

Conversational interfaces have recently become a ubiquitous element in both the personal sphere by easing access to services, and industrial environments by the automation of services, improved customer support and its corresponding cost savings. However, ...

2021

Flocking-enhanced social contagion

Ignacio Pagonabarraga Mora

Populations of mobile agents-animal groups, robot swarms, or crowds of people-self-organize into a large diversity of states as a result of information exchanges with their surroundings. While in many situations of interest the motion of the agents is driv ...

AMER PHYSICAL SOC2020