activity
20212026
most citedThe Complexity of Data-Driven Norm Synthesis and Revision

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2026

Engineering Reliable Autonomous Systems: Challenges and Solutions

Marie Farrell, Matt Luckcuck, Angelo Ferrando +28

Engineering reliable autonomous systems is an important and growing topic in computer science. As autonomous systems become more prevalent, easy-to-use techniques for building them…

cs.FL2026

Temporal Causal Models as a Model of Computation

Maksim Gladyshev, Natasha Alechina, Brian Logan

Causal models, also known as Structural Equation Models (SEM), are a well-known formalism for representing and reasoning about causal dependencies between events. In this paper, we…

cs.AI2025

Pushdown Reward Machines for Reinforcement Learning

Giovanni Varricchione, Toryn Q. Klassen, Natasha Alechina +3

Reward machines (RMs) are automata structures that encode (non-Markovian) reward functions for reinforcement learning (RL). RMs can reward any behaviour representable in regular la…

cs.AI2025

Probabilistic Strategy Logic with Degrees of Observability

Chunyan Mu, Nima Motamed, Natasha Alechina +1

There has been considerable work on reasoning about the strategic ability of agents under imperfect information. However, existing logics such as Probabilistic Strategy Logic are u…

cs.AI2025

Temporal Causal Reasoning with (Non-Recursive) Structural Equation Models

Maksim Gladyshev, Natasha Alechina, Mehdi Dastani +2

Structural Equation Models (SEM) are the standard approach to representing causal dependencies between variables in causal models. In this paper we propose a new interpretation of…

cs.RO2024

Grand Challenges in the Verification of Autonomous Systems

Kevin Leahy, Hamid Asgari, Louise A. Dennis +6

Autonomous systems use independent decision-making with only limited human intervention to accomplish goals in complex and unpredictable environments. As the autonomy technologies…

cs.LG2024

Maximally Permissive Reward Machines

Giovanni Varricchione, Natasha Alechina, Mehdi Dastani +1

Reward machines allow the definition of rewards for temporally extended tasks and behaviors. Specifying "informative" reward machines can be challenging. One way to address this is…

cs.CC2021★ 1 cited

The Complexity of Data-Driven Norm Synthesis and Revision

Davide Dell'Anna, Natasha Alechina, Brian Logan +3

Norms have been widely proposed as a way of coordinating and controlling the activities of agents in a multi-agent system (MAS). A norm specifies the behaviour an agent should foll…