activity
20192024
most citedNon-Bayesian Social Learning with Uncertain Models

30 citations · 30 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV2024

StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments

Sean Kulinski, Nicholas R. Waytowich, James Z. Hare +1

Spatial reasoning tasks in multi-agent environments such as event prediction, agent type identification, or missing data imputation are important for multiple applications (e.g., a…

cs.AI2020

A General Framework for Distributed Inference with Uncertain Models

James Z. Hare, Cesar A. Uribe, Lance Kaplan +1

This paper studies the problem of distributed classification with a network of heterogeneous agents. The agents seek to jointly identify the underlying target class that best descr…

stat.ME2019

Non-Bayesian Social Learning with Gaussian Uncertain Models

James Z. Hare, Cesar Uribe, Lance Kaplan +1

Non-Bayesian social learning theory provides a framework for distributed inference of a group of agents interacting over a social network by sequentially communicating and updating…

cs.AI2019★ 30 cited

Non-Bayesian Social Learning with Uncertain Models

James Z. Hare, Cesar A. Uribe, Lance Kaplan +1

Non-Bayesian social learning theory provides a framework that models distributed inference for a group of agents interacting over a social network. In this framework, each agent it…

math.OC2019

Non-Bayesian Social Learning with Uncertain Models over Time-Varying Directed Graphs

César A. Uribe, James Z. Hare, Lance Kaplan +1

We study the problem of non-Bayesian social learning with uncertain models, in which a network of agents seek to cooperatively identify the state of the world based on a sequence o…