Modeling Ambiguity in a Multi-Agent System
Christof Monz
Abstract
This paper investigates the formal pragmatics of ambiguous expressions by modeling ambiguity in a multi-agent system. Such a framework allows us to give a more refined notion of the kind of information that is conveyed by ambiguous expressions. We analyze how ambiguity affects the knowledge of the dialog participants and, especially, what they know about each other after an ambiguous sentence has been uttered. The agents communicate with each other by means of a TELL-function, whose application is constrained by an implementation of some of Grice's maxims. The information states of the multi-agent system itself are represented as a Kripke structures and TELL is an update function on those structures. This framework enables us to distinguish between the information conveyed by ambiguous sentences vs. the information conveyed by disjunctions, and between semantic ambiguity vs. perceived ambiguity.
Create a lesson
Related papers
RetireOPD: Self-Retiring On-Policy Distillation for Agentic Reinforcement Learning
Yan Yu, Zhengxi Lu, Yizhou Liu et al.
Harm Laundering in GPT Models: Evidence That Gender Discrimination Is Transformed Rather Than Reduced Across Safety-Trained Generations
Sarah Wyer, Sue Black, Noura Al Moubayed
dQwen3.5: Hybrid-Attention Diffusion Language Models
Anton Xue, Litu Rout, Aditya Akella et al.
On-Demand Attention: Language Models Know When to Recall
Haibo Feng, Ruiqi Liang, Hanyang Peng et al.
Summarization Bias: The Directional Collapse of Objective Projection into Told-Mode Labels in Large Language Models --- A Conceptual Framework and Registered Test Protocol
Levent Bulut
HerHealthEval: Evaluating Multilingual and Register-Sensitive Understanding of Women's Health Communication
Hassan Saeed Hassan Albattra, Mazen Mohammed Bahgat, Rahatara Ferdousi et al.