Related papers: Relational Action Bases: Formalization, Effective …

Knowledge and Action Bases (KABs) have been recently proposed as a formal framework to capture the dynamics of systems which manipulate Description Logic (DL) Knowledge Bases (KBs) through action execution. In this work, we enrich the KAB…

We study the extension of relational multiagent systems (RMASs), where agents manipulate full-fledged relational databases, with data types and facets equipped with domain-specific, rigid relations (such as total orders). Specifically, we…

Description Logic Knowledge and Action Bases (KABs) have been recently introduced as a mechanism that provides a semantically rich representation of the information on the domain of interest in terms of a DL KB and a set of actions to…

Role-Based Access Control (RBAC) is a popular authorization model used to manage data-access constraints in a wide range of systems. RBAC usually defines the static view on the access rights. However, to ensure dependability of a system, it…

We propose DAB -- a data-aware extension of BPMN where the process operates over case and persistent data (partitioned into a read-only database called catalog and a read-write database called repository). The model trades off between…

We propose DAB -- a data-aware extension of the BPMN de-facto standard with the ability of operating over case and persistent data (partitioned into a read-only catalog and a read-write repository), and that balances between expressiveness…

Distributed storage systems and databases are widely used by various types of applications. Transactional access to these storage systems is an important abstraction allowing application programmers to consider blocks of actions (i.e.,…

Ensuring the safety of reinforcement learning (RL) policies in high-stakes environments requires not only formal verification but also interpretability and targeted falsification. While model checking provides formal guarantees, its…

Sequential experiments are often characterized by an exploration-exploitation tradeoff that is captured by the multi-armed bandit (MAB) framework. This framework has been studied and applied, typically when at each time period feedback is…

Regular model checking is a technique for the verification of infinite-state systems whose configurations can be represented as finite words over a suitable alphabet. The form we are studying applies to systems whose set of initial…

One of the most widespread framework for the management of access-control policies is Administrative Role Based Access Control (ARBAC). Several automated analysis techniques have been proposed to help maintaining desirable security…

Description logic Knowledge and Action Bases (KAB) are a mechanism for providing both a semantically rich representation of the information on the domain of interest in terms of a description logic knowledge base and actions to change such…

In reinforcement learning (RL) research, it is common to assume access to direct online interactions with the environment. However in many real-world applications, access to the environment is limited to a fixed offline dataset of logged…

Relational properties arise in many settings: relating two versions of a program that use different data representations, noninterference properties for security, etc. The main ingredient of relational verification, relating aligned pairs…

The cooperative Multi-A gent R einforcement Learning (MARL) with permutation invariant agents framework has achieved tremendous empirical successes in real-world applications. Unfortunately, the theoretical understanding of this MARL…

In this paper, we consider a transfer Reinforcement Learning (RL) problem in continuous state and action spaces, under unobserved contextual information. For example, the context can represent the mental view of the world that an expert…

Risk-based authentication (RBA) is an adaptive security measure to strengthen password-based authentication. RBA monitors additional implicit features during password entry such as device or geolocation information, and requests additional…

Agent-based models (ABMs) are simulation models used in economics to overcome some of the limitations of traditional frameworks based on general equilibrium assumptions. However, agents within an ABM follow predetermined 'bounded rational'…

During the last two decades, it has been increasingly acknowledged that the engineering of information systems usually requires a huge effort in integrating master data and business processes. This has led to a plethora of proposals, both…

Learning a control policy capable of adapting to time-varying and potentially evolving system dynamics has been a great challenge to the mainstream reinforcement learning (RL). Mainly, the ever-changing system properties would continuously…