16 citations · 37 across the 7 of their papers we have counts for
7 papers
Reinforcement Learning with Stochastic Reward Machines
Jan Corazza, Ivan Gavran, Daniel Neider
Reward machines are an established tool for dealing with reinforcement learning problems in which rewards are sparse and depend on complex sequences of actions. However, existing a…
Accessible Smart Contracts Verification: Synthesizing Formal Models with Tamed LLMs
Jan Corazza, Ivan Gavran, Gabriela Moreira +1
When blockchain systems are said to be trustless, what this really means is that all the trust is put into software. Thus, there are strong incentives to ensure blockchain software…
Lassie: HOL4 Tactics by Example
Heiko Becker, Nathaniel Bos, Ivan Gavran +2
Proof engineering efforts using interactive theorem proving have yielded several impressive projects in software systems and mathematics. A key obstacle to such efforts is the requ…
Joint Inference of Reward Machines and Policies for Reinforcement Learning
Zhe Xu, Ivan Gavran, Yousef Ahmad +4
Incorporating high-level knowledge is an effective way to expedite reinforcement learning (RL), especially for complex tasks with sparse rewards. We investigate an RL problem where…
Learning Linear Temporal Properties
Daniel Neider, Ivan Gavran
We present two novel algorithms for learning formulas in Linear Temporal Logic (LTL) from examples. The first learning algorithm reduces the learning task to a series of satisfiabi…
Precise but Natural Specification for Robot Tasks
Ivan Gavran, Brendon Boldt, Eva Darulova +1
We present Flipper, a natural language interface for describing high-level task specifications for robots that are compiled into robot actions. Flipper starts with a formal core la…
The Robot Routing Problem for Collecting Aggregate Stochastic Rewards
Rayna Dimitrova, Ivan Gavran, Rupak Majumdar +2
We propose a new model for formalizing reward collection problems on graphs with dynamically generated rewards which may appear and disappear based on a stochastic model. The *robo…