6 papers
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…
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…
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…
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…
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…
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…