no code implementations • 14 Oct 2024 • John Mern, Anthony Corso, Damian Burch, Kurt House, Jef Caers
Planning data acquisition under wrong geological priors is likely to be inefficient since the estimated uncertainty on the target property is incorrect, hence uncertainty may not be reduced at all.
1 code implementation • 20 Jun 2024 • Harrison Delecki, Marc R. Schlichting, Mansur Arief, Anthony Corso, Marcell Vazquez-Chanlatte, Mykel J. Kochenderfer
Validating safety-critical autonomous systems in high-dimensional domains such as robotics presents a significant challenge.
1 code implementation • 1 May 2024 • Robert J. Moss, Arec Jamgochian, Johannes Fischer, Anthony Corso, Mykel J. Kochenderfer
To plan safely in uncertain environments, agents must balance utility with safety constraints.
1 code implementation • 6 Mar 2024 • Max Lamparth, Anthony Corso, Jacob Ganz, Oriana Skylar Mastro, Jacquelyn Schneider, Harold Trinkunas
To test this potential and scrutinize the use of LLMs for such purposes, we use a new wargame experiment with 214 national security experts designed to examine crisis escalation in a fictional U. S.-China scenario and compare the behavior of human player teams to LLM-simulated team responses in separate simulations.
1 code implementation • 30 Oct 2023 • Arec Jamgochian, Hugo Buurmeijer, Kyle H. Wray, Anthony Corso, Mykel J. Kochenderfer
Optimal plans in Constrained Partially Observable Markov Decision Processes (CPOMDPs) maximize reward objectives while satisfying hard cost constraints, generalizing safe planning under state and transition uncertainty.
1 code implementation • 9 Oct 2023 • Nick DiSanto, Anthony Corso, Benjamin Sanders, Gavin Harding
While transformers have pioneered attention-driven architectures as a cornerstone of language modeling, their dependence on explicitly contextual information underscores limitations in their abilities to tacitly learn overarching textual themes.
no code implementations • 20 Jul 2023 • Anthony Corso, David Karamadian, Romeo Valentin, Mary Cooper, Mykel J. Kochenderfer
As machine learning (ML) systems increasingly permeate high-stakes settings such as healthcare, transportation, military, and national security, concerns regarding their reliability have emerged.
no code implementations • 17 Jul 2023 • Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe
In this white paper, we synthesize key points made during presentations and discussions from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for Research on Computation and Society at Harvard University on October 20-21, 2022.
1 code implementation • 31 May 2023 • Robert J. Moss, Anthony Corso, Jef Caers, Mykel J. Kochenderfer
BetaZero learns offline approximations that replace heuristics to enable online decision making in long-horizon problems.
1 code implementation • 17 May 2023 • Harrison Delecki, Anthony Corso, Mykel J. Kochenderfer
Estimating the distribution over failures is a key step in validating autonomous systems.
1 code implementation • 26 Apr 2023 • Alessandro Pinto, Anthony Corso, Edward Schmerling
We apply a compositional formal modeling and verification method to an autonomous aircraft taxi system.
1 code implementation • 23 Dec 2022 • Arec Jamgochian, Anthony Corso, Mykel J. Kochenderfer
Rather than augmenting rewards with penalties for undesired behavior, Constrained Partially Observable Markov Decision Processes (CPOMDPs) plan safely by imposing inviolable hard constraint value budgets.
no code implementations • 22 Nov 2022 • Anthony Corso, Kyu-Young Kim, Shubh Gupta, Grace Gao, Mykel J. Kochenderfer
An important step in the design of autonomous systems is to evaluate the probability that a failure will occur.
no code implementations • 25 Oct 2022 • Anthony Corso, Yizheng Wang, Markus Zechner, Jef Caers, Mykel J. Kochenderfer
This POMDP model can be used as a test bed to drive the development of novel decision-making algorithms for CCS operations.
no code implementations • 4 Feb 2022 • Chelsea Sidrane, Sydney Katz, Anthony Corso, Mykel J. Kochenderfer
When the forward model that produced the observations is nonlinear and stochastic, solving the inverse problem is very challenging.
no code implementations • 9 Dec 2020 • Anthony Corso, Mykel J. Kochenderfer
Safety validation is important during the development of safety-critical autonomous systems but can require significant computational effort.
no code implementations • 6 May 2020 • Anthony Corso, Robert J. Moss, Mark Koren, Ritchie Lee, Mykel J. Kochenderfer
Autonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-critical applications, but require rigorous testing before deployment.
no code implementations • 14 Apr 2020 • Anthony Corso, Ritchie Lee, Mykel J. Kochenderfer
In this work, we present a new safety validation approach that attempts to estimate the distribution over failures of an autonomous policy using approximate dynamic programming.
2 code implementations • 14 Apr 2020 • Anthony Corso, Mykel J. Kochenderfer
Our methodology is demonstrated for the safety validation of an autonomous vehicle in the context of an unprotected left turn and a crosswalk with a pedestrian.
no code implementations • 8 Apr 2020 • Mark Koren, Anthony Corso, Mykel J. Kochenderfer
Validation is a key challenge in the search for safe autonomy.
no code implementations • 2 Aug 2019 • Anthony Corso, Peter Du, Katherine Driggs-Campbell, Mykel J. Kochenderfer
Determining possible failure scenarios is a critical step in the evaluation of autonomous vehicle systems.