Understanding dynamic agent's reasoning

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2007

Autores

lau, n (Autor) Outra; reis, lp (Autor) FEUP; certo, j (Autor) Outra

Ata de Conferência Internacional

Título: PROGRESS IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS

Páginas: 542-551

13th Portuguese Conference on Artificial Intelligence

Guimaraes, PORTUGAL, DEC 03-07, 2007

Indexação

ISI Web of Knowledge - 4 Citações

Scopus - 4 Citações

Classificação Científica

FOS: Ciências exactas e naturais > Ciências da computação e da informação

Outras Informações

ID Authenticus: P-004-EFQ

DOI: 10.1007/978-3-540-77002-2_46

Abstract (EN): Heterogeneous agents that execute in dynamic, uncertain, partially cooperative, partially adversely environments have to take their decisions rapidly with an incomplete knowledge of actual environment conditions. This paper discusses different level of abstractions in agent's development for this type of domain, explains the principles of offline debugging and employs these principles in robotic agent's teams through the use of a new visual debugging tool. We argue that during the development of such complex agents, understanding agent reasoning is of crucial importance to the developer and that such understanding can only be done, in most of the cases, using an offline analysis of the agent's decisions. In order for the developer to rapidly perceive agent's reasoning we advocate visual debugging of the agent knowledge and reasoning at several levels of abstraction and at several different functional views. These principles have been applied with success in the context of a robotic soccer 2D simulation league team through the development of tools and extensive use of these analysis principles.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 10