18 citations · 26 across the 3 of their papers we have counts for
3 papers
cs.AI2019★ 18 cited
The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data
Amanda Gentzel, Dan Garant, David Jensen
Causal inference is central to many areas of artificial intelligence, including complex reasoning, planning, knowledge-base construction, robotics, explanation, and fairness. An ac…
cs.MA2017★ 1 cited
Context-Based Concurrent Experience Sharing in Multiagent Systems
Dan Garant, Bruno da Silva, Victor Lesser +1
One of the key challenges for multi-agent learning is scalability. In this paper, we introduce a technique for speeding up multi-agent learning by exploiting concurrent and increme…
cs.AI2016★ 7 cited
Evaluating Causal Models by Comparing Interventional Distributions
Dan Garant, David Jensen
The predominant method for evaluating the quality of causal models is to measure the graphical accuracy of the learned model structure. We present an alternative method for evaluat…