5 citations · 8 across the 12 of their papers we have counts for
14 papers
SPLASH! Sample-efficient Preference-based inverse reinforcement learning for Long-horizon Adversarial tasks from Suboptimal Hierarchical demonstrations
Peter Crowley, Zachary Serlin, Tyler Paine +3
Inverse Reinforcement Learning (IRL) presents a powerful paradigm for learning complex robotic tasks from human demonstrations. However, most approaches make the assumption that ex…
Accelerating Proximal Policy Optimization Learning Using Task Prediction for Solving Environments with Delayed Rewards
Ahmad Ahmad, Mehdi Kermanshah, Kevin Leahy +6
In this paper, we tackle the challenging problem of delayed rewards in reinforcement learning (RL). While Proximal Policy Optimization (PPO) has emerged as a leading Policy Gradien…
A Flexible and Efficient Temporal Logic Tool for Python: PyTeLo
Gustavo A. Cardona, Kevin Leahy, Makai Mann +1
Temporal logic is an important tool for specifying complex behaviors of systems. It can be used to define properties for verification and monitoring, as well as goals for synthesis…
How to Train Your Neural Control Barrier Function: Learning Safety Filters for Complex Input-Constrained Systems
Oswin So, Zachary Serlin, Makai Mann +4
Control barrier functions (CBF) have become popular as a safety filter to guarantee the safety of nonlinear dynamical systems for arbitrary inputs. However, it is difficult to cons…
Safety-Aware Task Composition for Discrete and Continuous Reinforcement Learning
Kevin Leahy, Makai Mann, Zachary Serlin
Compositionality is a critical aspect of scalable system design. Reinforcement learning (RL) has recently shown substantial success in task learning, but has only recently begun to…
STL: Surprisingly Tricky Logic (for System Validation)
Ho Chit Siu, Kevin Leahy, Makai Mann
Much of the recent work developing formal methods techniques to specify or learn the behavior of autonomous systems is predicated on a belief that formal specifications are interpr…
Lightweight Online Learning for Sets of Related Problems in Automated Reasoning
Haoze Wu, Christopher Hahn, Florian Lonsing +3
We present Self-Driven Strategy Learning (), a lightweight online learning methodology for automated reasoning tasks that involve solving a set of related problems.…
Uncertainty Quantification for Recursive Estimation in Adaptive Safety-Critical Control
Max H. Cohen, Makai Mann, Kevin Leahy +1
In this paper, we present a framework for online parameter estimation and uncertainty quantification in the context of adaptive safety-critical control. The key insight enabling ou…
Learning Minimally-Violating Continuous Control for Infeasible Linear Temporal Logic Specifications
Mingyu Cai, Makai Mann, Zachary Serlin +2
This paper explores continuous-time control synthesis for target-driven navigation to satisfy complex high-level tasks expressed as linear temporal logic (LTL). We propose a model-…
Automating System Configuration
Nestan Tsiskaridze, Maxwell Strange, Makai Mann +4
The increasing complexity of modern configurable systems makes it critical to improve the level of automation in the process of system configuration. Such automation can also impro…
lazybvtoint at the SMT Competition 2020
Yoni Zohar, Ahmed Irfan, Makai Mann +3
lazybvtoint is a new prototype SMT-solver, that will participate in the incremental and non-incremental tracks of the \qfbv logic.
Counterexample-Guided Prophecy for Model Checking Modulo the Theory of Arrays
Makai Mann, Ahmed Irfan, Alberto Griggio +2
We develop a framework for model checking infinite-state systems by automatically augmenting them with auxiliary variables, enabling quantifier-free induction proofs for systems th…
Smt-Switch: a solver-agnostic C++ API for SMT Solving
Makai Mann, Amalee Wilson, Cesare Tinelli +1
This extended abstract describes work in progress on Smt-Switch, an open-source, solver-agnostic API for SMT solving. Smt-Switch provides an abstract interface, which can be implem…
fault: A Python Embedded Domain-Specific Language For Metaprogramming Portable Hardware Verification Components
Lenny Truong, Steven Herbst, Rajsekhar Setaluri +8
While hardware generators have drastically improved design productivity, they have introduced new challenges for the task of verification. To effectively cover the functionality of…