The responsibility gap is a set of outcomes of a collective decision-making mechanism in which no single agent is individually responsible. In general, when designing a decision-making process, it is desirable to minimise the gap. The paper studies the class of mechanisms for which the gap is empty and proposes a concept of an elected dictatorship. It shows that, in a perfect information setting, the gap is empty if and only if the mechanism is an elected dictatorship. It also proves that in an imperfect information setting, the class of gap-free mechanisms is positioned strictly between two variations of the class of elected dictatorships.

Abstract Traditionally, the formulae in modal logic express properties of possible worlds. Prior introduced “egocentric” logics that capture properties of agents rather than of possible worlds. In such a setting, the article proposes the modality “know how to tell apart” and gives a complete logical system describing the interplay between this modality and the knowledge modality. An important contribution of this work is a new matrix-based technique for proving completeness theorems in an egocentric setting.

Abstract The article proposes de dicto and de re versions of ‘knowing-who’ modalities as well as studies the interplay between them and modalities ‘knows’ and ‘for all agents’. It shows that neither of these four modalities is definable through a combination of the three others. In addition, a sound and complete logical system describing the properties of de dicto ‘knows who’, ‘knows’ and ‘for all agents’ modalities is presented.

Many decision-making scenarios, e.g., public policy, healthcare, business, and disaster response, require accommodating the preferences of multiple stakeholders. We offer the first formal treatment of reasoning with multi-stakeholder qualitative preferences in a setting where stakeholders express their preferences in a qualitative preference language, e.g., CP-net, CI-net, TCP-net, CP-Theory. We introduce a query language for expressing queries against such preferences over sets of outcomes that satisfy specified criteria, e.g., ψ1PAψ2 (read loosely as the set of outcomes satisfying ψ1 that are preferred over outcomes satisfying ψ2 by a set of stakeholders A). Motivated by practical application scenarios, we introduce and analyze several alternative semantics for such queries, and examine their interrelationships. We provide a provably correct algorithm for answering multi-stakeholder qualitative preference queries using model checking in alternation-free μ-calculus. We present experimental results that demonstrate the feasibility of our approach.

The paper studies two forms of responsibility, seeing to it and being blamable, in the setting of strategic games with imperfect information. The paper shows that being blamable is definable through seeing to it, but not the other way around. In addition, it proposes a bimodal logical system that describes the interplay between the seeing to it modality and the individual knowledge modality.

Security games are an example of a successful real-world application of game theory. The paper defines blameworthiness of the defender and the attacker in security games using the principle of alternative possibilities and provides a sound and complete logical system for reasoning about blameworthiness in such games. Two of the axioms of this system capture the asymmetry of information in security games.

Logical systems containing knowledge and know-how modalities have been investigated in several recent works. Independently, epistemic modal logics in which every knowledge modality is labeled with a degree of uncertainty have been proposed. This article combines these two research lines by introducing a bimodal logic containing knowledge and know-how modalities, both labeled with a degree of uncertainty. The main technical results are soundness, completeness, and incompleteness of the proposed logical system with respect to two classes of semantics.

There are multiple notions of coalitional responsibility. The focus of this paper is on the blameworthiness defined through the principle of alternative possibilities: a coalition is blamable for a statement if the statement is true, but the coalition had a strategy to prevent it. The main technical result is a sound and complete bimodal logical system that describes properties of blameworthiness in one-shot games.

The paper proposes a bimodal logic that describes an interplay between distributed knowledge modality and coalition know-how modality. Unlike other similar systems, the one proposed here assumes perfect recall by all agents. Perfect recall is captured in the system by a single axiom. The main technical results are the soundness and the completeness theorems for the proposed logical system.

The article introduces a modal logic for reasoning about combined effect of economic policies imposed on a group of rational agents. Modalities in this language are labelled by policies applied to the players in a strategic game. The resulting logical system allows to reason about properties that are true in all Nash equilibria of the game modified by a specific policy. The main technical result is the completeness theorem for the proposed logical system.

The article investigates epistemic properties of information flow under communication protocols with a given topological structure of the communication network. The main result is a sound and complete logical system that describes all such properties. The system consists of a variation of the multi-agent epistemic logic S5 extended by a new network-specific Gateway axiom.

Although first proposed in the database theory as properties of functional dependencies between attributes, Armstrong’s axioms capture general principles of information flow by describing properties of dependencies between sets of pieces of information. This article generalizes Armstrong’s axioms to a setting in which there is a cost associated with information. The proposed logical system captures general principles of dependencies between pieces of information constrained by a given budget.

Diseases that have different underlying genetic risk component(s) may share similar phenotypes. Traditionally, disease classifications have focused on characterizing diseases based on sets of related phenotypes. As an example, type I diabetes and type II diabetes are both classified as a type of diabetes based on patients having high blood sugar over long periods of time. However, as our understanding of genetic contributions to disease susceptibility and progression evolves, we start noticing that diseases with similar symptoms may have completely different causes. For example, type II diabetes is due to insulin resistance while type I diabetes is caused by immune cells attacking insulin producing cells. As genetic data becomes more highly available, it becomes possible to classify diseases based on their genetic causative drivers instead of their phenotypes. In this study, we have (1) explored the relationship between 10 autoimmune diseases along with type II diabetes based on their genetic susceptibility information and compared such classifications to existing disease categorizations based on disease symptoms/phenotypes from Human Phenotype Ontology, NCI-thesaurus and the Disease Ontology, and (2) developed automated scripts to compute similarities and cluster diseases based on the specified criteria. Categorization based on genetic susceptibility can help identify diseases that share similar drug targets and benefit from similar diagnosis technologies. We hope to further develop our system to apply it to more disease categories.

In many applications, Knowledge Bases (KBs) contain confidential or private information (secrets). The KB should be able to use this secret information in its reasoning process but in answering user queries care must be exercised so that secrets are not revealed to unauthorized users. We consider this problem under the Open World Assumption (OWA) in a setting with multiple querying agents M 1 ,…, M m that can pose queries against the KB K and selectively share answers that they receive from K with one or more other querying agents. We assume that for each M i , the KB has a prespecified set of secrets S i that need to be protected from M i . Communication between querying agents is modeled by a communication graph, a directed graph with self-loops. We introduce a general framework and propose an approach to secrecy-preserving query answering based on sound and complete proof systems. The idea is to hide the truthful answer from a querying agent M i by feigning ignorance without lying (i.e., to provide the answer ‘Unknown’ to a query q if it needs to be protected. Under the OWA, a querying agent cannot distinguish between the case that q is being protected (for reasons of secrecy) and the case that it cannot be inferred from K . In the pre-query stage we compute a set of envelopes E 1 , …, E m (restricted to a finite subset of the set of formulae that are entailed by K ) so that S i ⊆ E i , and a query α posed by agent M i can be answered truthfully whenever α ∉ E i and ¬ α ∉ E i . After the pre-query stage, the envelope is updated as needed. We illustrate this approach with two simple cases: the Propositional Horn KBs and the Description Logic AL KBs.