A System to Maintain Knowledge Bases of Intelligent Agents in DLV's Weak Constraints

J.C. Acosta Guadarrama (Germany)


Knowledge Management; Knowledge Representation and Reasoning; Logic Programming and ASP; Model-based Reasoning; Intelligent Agents and Systems


Updating agents’ knowledge bases is an important topic in Artificial Intelligence and a key problem of knowledge rep resentation and reasoning. One of the latest ideas to up date logic programs is to use abduction by means of Min imal Generalised Answer Sets (MGAS). MGAS provide a more general and flexible semantics than standard ASP , and we propose it to overcome disadvantages of previous approaches as well as to simplify both the semantics def inition and its implementation. Moreover, the author pro vides a link to a modest online prototype of the seman tics here introduced. This prototype models updates in a well-known Disjunctive Datalog, DLV, which is an imple mentation (solver) for Answer Set Programming. Accord ingly, the two-fold contribution of this paper is showing a simpler theoretical framework characterised in DLV’s weak constraints, as well as an outline of the basic structure of its implementation, description of the employed technology.

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