INVESTIGADORES
CHESÑEVAR Carlos Ivan
artículos
Título:
An Argument-based Framework to Model an Agent¿s Beliefs in a Dynamic Environment
Autor/es:
MARCELA CAPOBIANCO; CARLOS IVÁN CHESÑEVAR; GUILLERMO SIMARI,
Revista:
LECTURE NOTES IN COMPUTER SCIENCE
Editorial:
Springer Verlag, Germany
Referencias:
Lugar: Berlin; Año: 2005 vol. 3366 p. 95 - 110
ISSN:
0302-9743
Resumen:
One of the most difficult problems in multiagent systems involves representing knowledge and beliefs of agents in dynamic environments.New perceptions modify an agents current knowledge about the world, and consequently its beliefs. Such revision and updating process should be performed efficiently by the agent, particularly in the context of real time constraints. This paper introduces an argument-based logic programming language called Observation-based Defeasible Logic Programming (ODeLP). An ODeLP program is used to represent an agents knowledge in the context of a multiagent system. The beliefs of the agent are modeled with warranted goals computed on the basis of the agents program. New perceptions from the environment result in changes in the agents knowledge handled by a simple but effective updating strategy. The process of computing beliefs in a changing environment is made computationally attractive by integrating a dialectical database with the agents program, providing precompiled information about inferences. We present algorithms for creation and use of dialectical databases.Observation-based Defeasible Logic Programming (ODeLP). An ODeLP program is used to represent an agents knowledge in the context of a multiagent system. The beliefs of the agent are modeled with warranted goals computed on the basis of the agents program. New perceptions from the environment result in changes in the agents knowledge handled by a simple but effective updating strategy. The process of computing beliefs in a changing environment is made computationally attractive by integrating a dialectical database with the agents program, providing precompiled information about inferences. We present algorithms for creation and use of dialectical databases.

