Modeling and Verifying Probabilistic Social Commitments in Multi-Agent Systems
Notice bibliographique
Résumé
Interaction among autonomous agents in Multi-Agent Systems (MASs) is the key aspect for solving complex problems that an individual agent cannot handle alone. In this context, social approaches, as opposed to the mental approaches, have recently received a considerable attention in the area of agent communication. They exploit observable social \ncommitments to develop a verifiable formal semantics by which communication protocols can be specified. However, existing approaches for defining social commitments tend to \nassume an absolute guarantee of correctness so that systems run in a certain manner. That is, social commitments have always been modeled with the assumption of certainty. Moreover, the widespread use of MASs increases the interest to explore the interactions between different aspects of the participating agents such as the interaction between agents’ knowledge and social commitments in the presence of uncertainty. This results in having a gap, in the literature of agent communication, on modeling and verifying social commitments in probabilistic settings. \n \nIn this thesis, we aim to address the above-mentioned problems by presenting a practical formal framework that is capable of handling the problem of uncertainty in social \ncommitments. First, we develop an approach for representing, reasoning about, and verifying \nprobabilistic social commitments in MASs. This includes defining a new logic called the probabilistic logic of commitments (PCTLC), and a reduction-based model checking \nprocedure for verifying the proposed logic. In the reduction technique, the problem of model checking PCTLC is transformed into the problem of model checking PCTL so that \nthe use of the PRISM (Probabilistic Symbolic Model Checker) is made possible. Formulae of PCTLC are interpreted over an extended version of the probabilistic interpreted systems \nformalism. Second, we extend the work we proposed for probabilistic social commitments to be able to capture and verify the interactions between knowledge and commitments. \nProperties representing the interactions between the two aspects are expressed in a new developed logic called the probabilistic logic of knowledge and commitment (PCTLkc). \nThird, we develop an adequate semantics for the group social commitments, for the first time in the literature, and integrate it into the framework. We then introduce an improved version of PCTLkc and extend it with operators for the group knowledge and group social commitments. The new refined logic is called PCTLkc+. In each of the latter stages, we respectively develop a new version of the probabilistic interpreted systems over which the \npresented logic is interpreted, and introduce a new reduction-based verification technique to verify the proposed logic. To evaluate our proposed work, we implement the proposed verification techniques on top of the PRISM model checker and apply them on several case studies. The results demonstrate the usefulness and effectiveness of our proposed work.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».