Logotipo do repositório
 

Publicação:
An Iowa Gambling Task-based experiment applied to robots: A Study on Long-term Decision Making

Carregando...
Imagem de Miniatura

Orientador

Coorientador

Pós-graduação

Curso de graduação

Título da Revista

ISSN da Revista

Título de Volume

Editor

Tipo

Trabalho apresentado em evento

Direito de acesso

Resumo

Designing a robot's decision-making process is challenging because it is still not completely understood even in humans. However, it is a fundamental process in the search for autonomous agents. When making decisions, we consider the short and long-term consequences of our actions, but some impairments prevent some people from seeing in the long run. Using as an inspiration an experiment carried out with humans in which decision-making is evaluated under the uncertainty of premises and results, rewards, and punishments, we created an equivalent robotics experiment. To model our agent's state, we use a set of drives. Our agent's goal is to reduce the distance between its homeostasis state and its needs. We trained a simulated robot with reinforcement learning, showing that long-term assessment agents can survive longer while satisfying other needs.

Descrição

Palavras-chave

Action selection and planning, Exploration and Play, Intrinsic Motivation, Models of emotions and internal states

Idioma

Inglês

Como citar

IEEE International Conference on Development and Learning, ICDL 2021.

Itens relacionados

Financiadores

Coleções

Unidades

Departamentos

Cursos de graduação

Programas de pós-graduação