Anytime BDI: a time-bounded agent architecture

• Ano de defesa: 2022
• Autor(a) principal: Stabile Junior, Márcio Fernando
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Agent profiling; Agentes autônomos; Agentes BDI; Algoritmos anytime; Anytime algorithms; Autonomous agents; BDI agents; Profiling de agentes
• Link de acesso: https://www.teses.usp.br/teses/disponiveis/45/45134/tde-31012023-101712/

When integrating BDI agents into environments where the agent\'s response time interferes with the quality of their actions, the problem of lack of control over the agent\'s processing time becomes apparent. As there is no way to perform this control, there is no guarantee that the agent will be able to deliberate on the perceived information and perform an action in the environment within an expected time-bound. In order to provide this type of control over the processing time of BDI agents, this work presents a BDI agent model called Anytime BDI. This model uses anytime algorithms, profiling techniques, and multiobjective optimization techniques to ensure that the agent executes actions in the environment within a pre-established time-bound, minimizing the loss of quality of actions resulting from this control. Through the implementation of this model in Jason language and appropriate statistical validations, we show that there are scenarios where we can increase the agent\'s quality and scenarios where we can reduce the agent\'s processing time without prejudice to the agent\'s response.