Obtaining Plan Traces from Natural Language Conversations in a Healthcare Chatbot - Silva, Bianca Precebes da; Menezes, Maria Viviane de; Cruz, Lívia Almada; Pinho, Bruno da Silva; Sousa, Luis Fernando Oliveira (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC); 2025: Anais do XXII Encontro Nacional de Inteligência Artificial e ComputacionalDO - 10.5753/eniac.2025.14239, 2025)
Automated Planning is a subarea of Artificial Intelligence (AI) that studies the deliberative process of choosing actions for an agent to achieve its goals. A planner is a problem-solving algorithm that takes as input a high-level description of the agent and its environment (planning domain) and produces a sequence of actions (plan) that moves the agent from an initial state to a goal state. Acquiring a planning domain can be performed using algorithms that learn the domain description from a kind of specific data (plan traces). Obtaining such plan traces is difficult and a viable strategy is to extract it from Natural Language information. This work aims to build a database of plan traces from Natural Language dialogue data. These data represent conversations between real users and a healthcare chatbot.