Publications associées à Agent-based computational economics

Stochastic pairwise preference convergence in Bayesian agents

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 ...

2024

Social-Transmotion: Promptable Human Trajectory Prediction

Alexandre Massoud Alahi, Saeed Saadatnejad, Yang Gao, Kaouther Messaoud Ben Amor

Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

2024

Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

Christoph Koch, Zilu Tian, Val Tannen, Peter Lindner

We generalize the bulk-synchronous parallel (BSP) processing model to make it better support agent-based simulations. Such simulations frequently exhibit hierarchical structure in their communication patterns which can be exploited to improve performance. ...

2023

A subcellular biochemical model for T6SS dynamics reveals winning competitive strategies

Yuexia Luna Lin

The type VI secretion system (T6SS) is a broadly distributed interbacterial weapon that can be used to eliminate competing bacterial populations. Although unarmed target populations are typically used to study T6SS function in vitro, bacteria most likely e ...

OXFORD UNIV PRESS2023

Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations

Zilu Tian

Agent-based simulations have been widely applied in many disciplines, by scientists and engineers alike. Scientists use agent-based simulations to tackle global problems, including alleviating poverty, reducing violence, and predicting the impact of pandem ...

EPFL2023

Multi-agent actor-critic with time dynamical opponent model

Olga Fink, Qin Wang

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 ...

2023

Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

Henry Markram, Eilif Benjamin Muller, Srikanth Ramaswamy, Michael Reimann, James Gonzalo King, Rajnish Ranjan, Armando Romani, Mustafa Anil Tuncel, Aleksandra Zuzanna Teska, Polina Litvak, Matthias Wolf, Felix Schürmann, Daniel Keller, Werner Alfons Hilda Van Geit, Pramod Shivaji Kumbhar, Alexis Arnaudon, Jean-Denis Georges Emile Courcol, Giuseppe Chindemi, András Ecker, Michael Emiel Gevaert, Christian Andreas Rössert, Vishal Sood, Sirio Bolaños Puchet, James Bryden Isbister, Judit Planas Carbonell, Daniela Egas Santander, Omar Awile, Maria Reva, Joni Henrikki Herttuainen, Genrich Ivaska, Natali Barros Zulaica, Samuel Lieven D. Lapere, Christoph Pokorny, Elvis Boci, Thomas Brice Delemontex, Jorge Blanco Alonso, Tanguy Pierre Louis Damart, Alexander Dietz, Darshan Mandge, ,

Improved Cooperation by Exploiting a Common Signal

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 ...

International Foundation for Autonomous Agents and Multiagent Systems2022

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

Making the collective knowledge of chemistry open and machine actionable

Berend Smit, Luc Patiny, Kevin Maik Jablonka

Large amounts of data are generated in chemistry labs-nearly all instruments record data in a digital form, yet a considerable proportion is also captured non-digitally and reported in ways non-accessible to both humans and their computational agents. Chem ...

NATURE PORTFOLIO2022

A Downscaling Intercomparison Study: The Representation of Slope- and Ridge-Scale Processes in Models of Different Complexity

Varun Sharma, Franziska Gerber, Albertus Christiaan Kruyt, Dylan Stewart Reynolds

Spatially distributed meteorological information at the slope scale is relevant for many processes in complex terrain, yet information at this sub-km spatial resolution is difficult to obtain. While downscaling to kilometer resolutions is well described in ...

FRONTIERS MEDIA SA2022

3D Printed Acoustically Programmable Soft Microactuators

Mahmut Selman Sakar, Murat Kaynak, Amit Yedidia Dolev

The concept of creating all-mechanical soft microrobotic systems has great potential to address outstanding challenges in biomedical applications, and introduce more sustainable and multifunctional products. To this end, magnetic fields and light have been ...

2023

Towards sufficiency in housing: Agent-based model and transition scenarios

Margarita Agriantoni

Research problem: Housing is responsible for a considerable part of global resource consumption. In Switzerland, it accounts for almost one third of the country's CO2 emissions and half of the total energy demand. Thus, housing plays an important role in t ...

EPFL2022

No-regret learning in games with noisy feedback: Faster rates and adaptivity via learning rate separation

Volkan Cevher, Kimon Antonakopoulos, Ya-Ping Hsieh

We examine the problem of regret minimization when the learner is involved in a continuous game with other optimizing agents: in this case, if all players follow a no-regret algorithm, it is possible to achieve significantly lower regret relative to fully ...

2022

Vision-based Flocking in Aerial Robot Swarms

Fabian Maximilian Schilling

Aerial robot swarms have the potential to perform time-critical and dangerous tasks such as disaster response without compromising human safety. However, their reliance on external infrastructure such as global positioning for localization and wireless net ...

EPFL2022

Computational Concepts for Reconstructing and Simulating Brain Tissue

Srikanth Ramaswamy, Felix Schürmann, Jean-Denis Georges Emile Courcol

It has previously been shown that it is possible to derive a new class of biophysically detailed brain tissue models when one computationally analyzes and exploits the interdependencies or the multi-modal and multi-scale organization of the brain. These re ...

Springer2022

Exploring policy change through agent-based simulation

Raphaël Klein

Policymaking is a complex process that has been studied using policy process theories almost exclusively. These theories have been built using a large number of qualitative cases. Such methods are useful for theory building but remain limited for theory ex ...

EPFL2021

Tenants’ residential mobility in Switzerland: the role of housing functions

Claudia Rebeca Binder Signer, Anna Pagani, Ivo Philippe Baur

The interaction between residential preferences and dwellings is a complex system whose function thus far remains insufficiently explored. In this paper, we investigate housing functions as orchestrators of households’ residential mobility in the context o ...

2021

Fundamental study on microlayer dynamics in nucleate boiling

Lubomír Bures

Dynamics of nucleate boiling are strongly affected by the formation and behaviour of the microlayer, a layer of liquid underneath growing bubbles. As a result of its minute thickness, very high heat fluxes occur within the microlayer and its evaporation co ...

EPFL2021

Learning Optimal Impedance Control During Complex 3D Arm Movements

Sylvain Calinon

In daily life, humans use their limbs to perform various movements to interact with an external environment. Thanks to limb's variable and adaptive stiffness, humans can adapt their movements to unstable dynamics of the external environments. The underlyin ...

IEEE2021