Agents that learn how to generate arguments from other agents
Learning how to argue is a key ability for a negotiator agent. In this paper, we propose an approach that allows agents to learn how to build arguments by observing how other agents argue in a negotiation context. Particularly, our approach enables the agent to infer the rulesfor argument generation...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/6780 |
| Acceso en línea: | http://hdl.handle.net/11336/6780 |
| Access Level: | acceso abierto |
| Palabra clave: | Intelligent Agents Argumentation-Based Negotiation Fuzzy Generalized Association Rules Learning https://purl.org/becyt/ford/1.2 https://purl.org/becyt/ford/1 |
| Sumario: | Learning how to argue is a key ability for a negotiator agent. In this paper, we propose an approach that allows agents to learn how to build arguments by observing how other agents argue in a negotiation context. Particularly, our approach enables the agent to infer the rulesfor argument generation that other agents apply to build their arguments. To carry out this goal, the agent stores the arguments uttered by other agents and the facts of the negotiation context where each argument is uttered. Then, an algorithm for fuzzy generalized association rules is applied to discover the desired rules. This kind of algorithm allows us (a) to obtain general rules that can be applied to dierent negotiation contexts; and (b) to deal with the uncertainty about the knowledge of what facts of the context are taken into account by the agents. The experimental results showed that it is possible to infer argument generation rules from a reduced number of observed arguments. |
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