26 citations · 40 across the 10 of their papers we have counts for
10 papers
Towards Personalized Explanations for Health Simulations: A Mixed-Methods Framework for Stakeholder-Centric Summarization
Philippe J. Giabbanelli, Ameeta Agrawal
Modeling & Simulation (M&S) approaches such as agent-based models hold significant potential to support decision-making activities in health, with recent examples including the ado…
Mitigation of Gender and Ethnicity Bias in AI-Generated Stories through Model Explanations
Martha O. Dimgba, Sharon Oba, Ameeta Agrawal +1
Language models have been shown to propagate social bias through their output, particularly in the representation of gender and ethnicity. This paper investigates gender and ethnic…
From over-reliance to smart integration: using Large-Language Models as translators between specialized modeling and simulation tools
Philippe J. Giabbanelli, John Beverley, Istvan David +1
Large Language Models (LLMs) offer transformative potential for Modeling & Simulation (M&S) through natural language interfaces that simplify workflows. However, over-reliance risk…
Broadening Access to Simulations for End-Users via Large Language Models: Challenges and Opportunities
Philippe J. Giabbanelli, Jose J. Padilla, Ameeta Agrawal
Large Language Models (LLMs) are becoming ubiquitous to create intelligent virtual assistants that assist users in interacting with a system, as exemplified in marketing. Although…
Accelerating Hybrid Agent-Based Models and Fuzzy Cognitive Maps: How to Combine Agents who Think Alike?
Philippe J. Giabbanelli, Jack T. Beerman
While Agent-Based Models can create detailed artificial societies based on individual differences and local context, they can be computationally intensive. Modelers may offset thes…
Narrating Causal Graphs with Large Language Models
Atharva Phatak, Vijay K. Mago, Ameeta Agrawal +2
The use of generative AI to create text descriptions from graphs has mostly focused on knowledge graphs, which connect concepts using facts. In this work we explore the capability…
GPT-Based Models Meet Simulation: How to Efficiently Use Large-Scale Pre-Trained Language Models Across Simulation Tasks
Philippe J. Giabbanelli
The disruptive technology provided by large-scale pre-trained language models (LLMs) such as ChatGPT or GPT-4 has received significant attention in several application domains, oft…
Automatic Generation of Individual Fuzzy Cognitive Maps from Longitudinal Data
Maciej K Wozniak, Samvel Mkhitaryan, Philippe j. Giabbanelli
Fuzzy Cognitive Maps (FCMs) are computational models that represent how factors (nodes) change over discrete interactions based on causal impacts (weighted directed edges) from oth…
FCMpy: A Python Module for Constructing and Analyzing Fuzzy Cognitive Maps
Samvel Mkhitaryan, Philippe J. Giabbanelli, Maciej K. Wozniak +3
FCMpy is an open source package in Python for building and analyzing Fuzzy Cognitive Maps. More specifically, the package allows 1) deriving fuzzy causal weights from qualitative d…
An Algebra to Merge Heterogeneous Classifiers
Philippe J. Giabbanelli, Joseph G. Peters
In distributed classification, each learner observes its environment and deduces a classifier. As a learner has only a local view of its environment, classifiers can be exchanged a…