Evaluation of Alternative-Based Information Systems for Deliberative Polling using an Agentic Simulator
A new paper introduces the Agentic Bipolar Argumentation Simulator (ABAS) to evaluate information systems for large-scale deliberative polling. ABAS uses LLM-powered agents to simulate shareholder voting and justification processes, addressing the challenge of ensuring voters encounter a representative sample of arguments. Experiments show that certain weighting mechanisms, like reversed-PageRank, can resist strategic voting attacks that would otherwise collapse coverage. AI
IMPACT Introduces a novel simulation framework using LLM agents to tackle complex decision-making problems at scale.