3 citations · 4 across the 13 of their papers we have counts for
15 papers
About Time: Model-free Reinforcement Learning with Timed Reward Machines
Rajarshi Roy, Anirban Majumdar, Ritam Raha +2
Reward specification plays a central role in reinforcement learning (RL), guiding the agent's behavior. To express non-Markovian rewards, formalisms such as reward machines have be…
Probabilistic Model Checking: Applications and Trends
Marta Kwiatkowska, Gethin Norman, David Parker
Probabilistic model checking is an approach to the formal modelling and analysis of stochastic systems. Over the past twenty five years, the number of different formalisms and tech…
Learning Probabilistic Temporal Logic Specifications for Stochastic Systems
Rajarshi Roy, Yash Pote, David Parker +1
There has been substantial progress in the inference of formal behavioural specifications from sample trajectories, for example, using Linear Temporal Logic (LTL). However, these t…
Planning with Linear Temporal Logic Specifications: Handling Quantifiable and Unquantifiable Uncertainty
Pian Yu, Yong Li, David Parker +1
This work studies the planning problem for robotic systems under both quantifiable and unquantifiable uncertainty. The objective is to enable the robotic systems to optimally fulfi…
Expectation vs. Reality: Towards Verification of Psychological Games
Marta Kwiatkowska, Gethin Norman, David Parker +1
Game theory provides an effective way to model strategic interactions among rational agents. In the context of formal verification, these ideas can be used to produce guarantees on…
HSVI-based Online Minimax Strategies for Partially Observable Stochastic Games with Neural Perception Mechanisms
Rui Yan, Gabriel Santos, Gethin Norman +2
We consider a variant of continuous-state partially-observable stochastic games with neural perception mechanisms and an asymmetric information structure. One agent has partial inf…
Safe POMDP Online Planning among Dynamic Agents via Adaptive Conformal Prediction
Shili Sheng, Pian Yu, David Parker +2
Online planning for partially observable Markov decision processes (POMDPs) provides efficient techniques for robot decision-making under uncertainty. However, existing methods fal…
Partially Observable Stochastic Games with Neural Perception Mechanisms
Rui Yan, Gabriel Santos, Gethin Norman +2
Stochastic games are a well established model for multi-agent sequential decision making under uncertainty. In practical applications, though, agents often have only partial observ…
Point-Based Value Iteration for POMDPs with Neural Perception Mechanisms
Rui Yan, Gabriel Santos, Gethin Norman +2
The increasing trend to integrate neural networks and conventional software components in safety-critical settings calls for methodologies for their formal modelling, verification…
Symbolic Verification and Strategy Synthesis for Turn-based Stochastic Games
Marta Kwiatkowska, Gethin Norman, David Parker +1
Stochastic games are a convenient formalism for modelling systems that comprise rational agents competing or collaborating within uncertain environments. Probabilistic model checki…
Probabilistic Model Checking for Strategic Equilibria-based Decision Making: Advances and Challenges
Marta Kwiatkowska, Gethin Norman, David Parker +2
Game-theoretic concepts have been extensively studied in economics to provide insight into competitive behaviour and strategic decision making. As computing systems increasingly in…
Finite-horizon Equilibria for Neuro-symbolic Concurrent Stochastic Games
Rui Yan, Gabriel Santos, Xiaoming Duan +2
We present novel techniques for neuro-symbolic concurrent stochastic games, a recently proposed modelling formalism to represent a set of probabilistic agents operating in a contin…
Strategy Synthesis for Zero-Sum Neuro-Symbolic Concurrent Stochastic Games
Rui Yan, Gabriel Santos, Gethin Norman +2
Neuro-symbolic approaches to artificial intelligence, which combine neural networks with classical symbolic techniques, are growing in prominence, necessitating formal approaches t…
Correlated Equilibria and Fairness in Concurrent Stochastic Games
Marta Kwiatkowska, Gethin Norman, David Parker +1
Game-theoretic techniques and equilibria analysis facilitate the design and verification of competitive systems. While algorithmic complexity of equilibria computation has been ext…
Probabilistic Model Checking and Autonomy
Marta Kwiatkowska, Gethin Norman, David Parker
Design and control of autonomous systems that operate in uncertain or adversarial environments can be facilitated by formal modelling and analysis. Probabilistic model checking is…