Uncommon Belief in Rationality

Common knowledge/belief in rationality is the traditional standard assumption in analysing interaction among agents. This paper proposes a graph-based language for capturing significantly more complicated structures of higher-order beliefs that agents might have about the rationality of the other agents. The two main contributions are a solution concept that captures the reasoning process based on a given belief structure and an efficient algorithm for compressing any belief structure into a unique minimal form.

The Logic of Doxastic Strategies

In many real-world situations, there is often not enough information to know that a certain strategy will succeed in achieving the goal, but there is a good reason to believe that it will. The paper introduces the term ``doxastic'' for such strategies. The main technical contribution is a sound and complete logical system that describes the interplay between doxastic strategy and belief modalities.

De Re and De Dicto Knowledge in Egocentric Setting

Prior proposes the term "egocentric" for logical systems that study properties of agents rather than properties of possible worlds. In such a setting, the paper introduces two different modalities capturing de re and de dicto knowledge and proves that these two modalities are not definable through each other.

Shhh! The Logic of Clandestine Operations

An operation is called covert if it conceals the identity of the actor; it is called clandestine if the very fact that the operation is conducted is concealed. The paper proposes a formal semantics of clandestine operations and introduces a sound and complete logical system that describes the interplay between the distributed knowledge modality and a modality capturing coalition power to conduct clandestine operations.

From Intelligent Agents to Trustworthy Human-Centred Multiagent Systems

The Agents, Interaction and Complexity research group at the University of Southampton has a long track record of research in multiagent systems (MAS). We have made substantial scientific contributions across learning in MAS, game-theoretic techniques for coordinating agent systems, and formal methods for representation and reasoning. We highlight key results achieved by the group and elaborate on recent work and open research challenges in developing trustworthy autonomous systems and deploying human-centred AI systems that aim to support societal good.

What are Your Powers? -- Truth Set Algebras

The paper studies the interplay between modalities representing four different types of multistep strategies in the imperfect information setting. It introduces a new "truth set algebra'' technique for proving undefinability, which is significantly different from the existing techniques based on bisimulation. The newly proposed technique is used to prove the undefinability of each of the four modalities through a combination of the three others.

Budget-Constrained Coalition Strategies with Discounting

Discounting future costs and rewards is a common practice in accounting, game theory, and machine learning. In spite of this, existing logics for reasoning about strategies with cost and resource constraints do not account for discounting. The paper proposes a sound and complete logical system for reasoning about budget-constrained strategic abilities that incorporates discounting into its semantics.

If You're Happy, Then You Know It: The Logic of Happiness and Sadness

The article proposes a formal semantics of happiness and sadness modalities in imperfect information setting. It shows that these modalities are not definable through each other and gives a sound and complete axiomatization of their properties.

Epistemic Logic of Know-Who

The paper suggests a definition of "know who" as a modality using Grove-Halpern semantics of names. It also introduces a logical system that describes the interplay between modalities "knows who", "knows", and "for all agents". The main technical result is a completeness theorem for the proposed system.

Comprehension and Knowledge

The ability of an agent to comprehend a sentence is tightly connected to the agent's prior experiences and background knowledge. The paper suggests to interpret comprehension as a modality and proposes a complete bimodal logical system that describes an interplay between comprehension and knowledge modalities.