Interactions between normative systems and software cognitive agents. A formalization in temporal modal defeasible logic and its implementation

Sustainable computer systems require some flexibility to adapt to environmental unpredictable changes. A solution lies in autonomous software agents which can adapt autonomously to their environments. Though autonomy allows agents to decide which behavior to adopt, a disadvantage is a lack of control, and as a side effect even untrustworthiness: we want to keep some control over such autonomous agents. How to control autonomous agents while respecting their autonomy? A solution is to regulate agents’ behavior by norms. The normative paradigm makes it possible to control autonomous agents while respecting their autonomy, limiting untrustworthiness and augmenting system compliance. It can also facilitate the design of the system, for example, by regulating the coordination among agents. However, an autonomous agent will follow norms or violate them in some conditions. What are the conditions in which a norm is binding upon an agent? While autonomy is regarded as the driving force behind the normative paradigm, cognitive agents provide a basis for modeling the bindingness of norms. In order to cope with the complexity of the modeling of cognitive agents and normative bindingness, we adopt an intentional stance. Since agents are embedded into a dynamic environment, things may not pass at the same instant. Accordingly, our cognitive model is extended to account for some temporal aspects. Special attention is given to the temporal peculiarities of the legal domain such as, among others, the time in force and the time in efficacy of provisions. Some types of normative modifications are also discussed in the framework. It is noteworthy that our temporal account of legal reasoning is integrated to our commonsense temporal account of cognition. As our intention is to build sustainable reasoning systems running unpredictable environment, we adopt a declarative representation of knowledge. A declarative representation of norms will make it easier to update their system representation, thus facilitating system maintenance; and to improve system transparency, thus easing system governance. Since agents are bounded and are embedded into unpredictable environments, and since conflicts may appear amongst mental states and norms, agent reasoning has to be defeasible, i.e. new pieces of information can invalidate formerly derivable conclusions. In this dissertation, our model is formalized into a non-monotonic logic, namely into a temporal modal defeasible logic, in order to account for the interactions between normative systems and software cognitive agents.

Una implementazione della Logica Defeasible Temporale per il ragionamento giuridico

La presente tesi descrive l’implementazione in Java di un algoritmo per il ragionamento giuridico che cattura due sue importanti peculiarità: la defeasibility del ragionamento normativo e il concetto di tempo. “Defeasible” significa “ritrattabile” e sta ad indicare, appunto, quegli schemi di ragionamento nei quali è possibile rivedere o ritrattare le conclusioni tratte precedentemente. Il tempo è essenziale per un’accurata rappresentazione degli scenari presenti nel mondo reale e in particolare per gli scenari giuridici. I profili temporali delle norme sono essenzialmente due: (i) tempo esterno della norma, cioè il periodo durante il quale la norma è valida cioè appartiene al sistema giuridico; (ii) tempo interno della norma che fa riferimento al periodo in cui la norma si applica. In particolare quest’ultimo periodo di tempo coincide con il periodo in cui le condizioni presenti nella norma devono presentarsi affinché essa produca i suoi effetti. Inoltre, nella tesi viene presentata un’estensione della logica defeasible in grado di distinguere tra regole con effetti persistenti, che valgono non solo per l’istante in cui si verificano le premesse ma anche per ogni istante successivo, e regole con effetti transitori, che valgono per un singolo istante. L’algoritmo presentato in questa tesi presenta una complessità lineare nelle dimensioni della teoria in ingresso e può interagire con le applicazioni del web semantico poiché elabora teorie scritte in Rule-ML, un linguaggio basato su XML per la rappresentazione di regole.