Combining Answer Set Programs for Adaptive and Reactive Reasoning

Tony Ribeiro (1) , Katsumi Inoue (2) , Gauvain Bourgne (3)

1 SOKENDAI - Graduate University for Advanced Studies [Hayama]
2 NII - National Institute of Informatics
3 ACASA - Agents Cognitifs et Apprentissage Symbolique Automatique

In this paper we present a method to improve efficiency of ASP based system in dynamic context. Our proposal is a reasoning framework based on combination of ASP modules. This framework can be seen as a tool to assist the development of ASP based systems. Our final goal is to provide a general design pattern to help construction of efficient ASP based reasoning systems. In this paper, we first define a method to divide the wide program into different kinds of modules. Then, we show how meta-knowledge on these decomposition can be used for meta-reasoning. We discuss the benefit of this modular reasoning method through an example of multi-agent systems in a dynamic world. Using this example, we show that this method can elegantly allow agents to realise dynamic behaviour via introspective meta-reasoning. Finally, through experimental results we show that the framework can be used to improve efficiency of ASP based system in terms of reactivity and adaptability.

Mots clés: Dynamic System; Meta-Reasoning; Modular Logic Programming; Answer Set Programming; Developement Tool

Domaines: Intelligence artificielle [cs.AI]; Logique en informatique [cs.LO]; Système multi-agents [cs.MA]

Tony Ribeiro, Katsumi Inoue, Gauvain Bourgne. Combining Answer Set Programs for Adaptive and Reactive Reasoning. Theory and Practice of Logic Programming, 2013, 13 (4-5-Online-Supplement). ⟨hal-01562133⟩