AI Safety Gridworlds

27 November 2017

Papers citing "AI Safety Gridworlds"

44 / 144 papers shown

Title
Learning the Arrow of Time Nasim Rahaman Steffen Wolf Anirudh Goyal Roman Remme Yoshua Bengio 14 5 0 02 Jul 2019
Evolutionary Computation and AI Safety: Research Problems Impeding Routine and Safe Real-world Application of Evolution Joel Lehman 12 7 0 24 Jun 2019
Categorizing Wireheading in Partially Embedded Agents Arushi G. K. Majha Sayan Sarkar Davide Zagami 11 3 0 21 Jun 2019
Epistemic Risk-Sensitive Reinforcement Learning Hannes Eriksson Christos Dimitrakakis 27 29 0 14 Jun 2019
Transfer Learning by Modeling a Distribution over Policies Disha Shrivastava Eeshan Gunesh Dhekane Riashat Islam OOD OffRL 14 0 0 09 Jun 2019
A Perspective on Objects and Systematic Generalization in Model-Based RL Sjoerd van Steenkiste Klaus Greff Jürgen Schmidhuber OCL OffRL 17 31 0 03 Jun 2019
Defining Admissible Rewards for High Confidence Policy Evaluation Niranjani Prasad Barbara E. Engelhardt Finale Doshi-Velez OffRL 31 6 0 30 May 2019
Don't Forget Your Teacher: A Corrective Reinforcement Learning Framework M. Nazari Majid Jahani L. Snyder Martin Takáč OffRL OnRL 16 1 0 30 May 2019
Inverse Reinforcement Learning in Contextual MDPs Stav Belogolovsky Philip Korsunsky Shie Mannor Chen Tessler Tom Zahavy OffRL BDL 31 19 0 23 May 2019
A Human-Centered Approach to Interactive Machine Learning K. Mathewson 16 7 0 15 May 2019
Safer Deep RL with Shallow MCTS: A Case Study in Pommerman Bilal Kartal Pablo Hernandez-Leal Chao Gao Matthew E. Taylor OffRL 17 7 0 10 Apr 2019
Truly Batch Apprenticeship Learning with Deep Successor Features Donghun Lee Srivatsan Srinivasan Finale Doshi-Velez OffRL OOD 9 35 0 24 Mar 2019
Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention Bharat Prakash Mohit Khatwani Nicholas R. Waytowich T. Mohsenin OffRL 7 19 0 22 Mar 2019
Safety-Guided Deep Reinforcement Learning via Online Gaussian Process Estimation Jiameng Fan Wenchao Li OffRL OnRL GP 8 18 0 06 Mar 2019
Introspection Learning Chris R. Serrano Michael A. Warren 16 0 0 27 Feb 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 17 996 0 26 Feb 2019
Understanding Agent Incentives using Causal Influence Diagrams. Part I: Single Action Settings Tom Everitt Pedro A. Ortega Elizabeth Barnes Shane Legg CML 17 0 0 26 Feb 2019
Conservative Agency via Attainable Utility Preservation Alexander Matt Turner Dylan Hadfield-Menell Prasad Tadepalli 30 49 0 26 Feb 2019
Parenting: Safe Reinforcement Learning from Human Input Christopher Frye Ilya Feige 14 7 0 18 Feb 2019
Iroko: A Framework to Prototype Reinforcement Learning for Data Center Traffic Control Fabian Ruffy Michael Przystupa Ivan Beschastnikh 22 31 0 24 Dec 2018
Building Ethically Bounded AI F. Rossi Nicholas Mattei 8 75 0 10 Dec 2018
Scalable agent alignment via reward modeling: a research direction Jan Leike David M. Krueger Tom Everitt Miljan Martic Vishal Maini Shane Legg 34 397 0 19 Nov 2018
Integrative Biological Simulation, Neuropsychology, and AI Safety G. Sarma A. Safron Nick J. Hay 14 2 0 07 Nov 2018
Formal Verification of Neural Network Controlled Autonomous Systems Xiaowu Sun Haitham Khedr Yasser Shoukry 11 134 0 31 Oct 2018
Assessing Generalization in Deep Reinforcement Learning Charles Packer Katelyn Gao Jernej Kos Philipp Krahenbuhl V. Koltun D. Song OffRL 18 233 0 29 Oct 2018
The Faults in Our Pi Stars: Security Issues and Open Challenges in Deep Reinforcement Learning Vahid Behzadan Arslan Munir 19 27 0 23 Oct 2018
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration Ritesh Noothigattu Djallel Bouneffouf Nicholas Mattei Rachita Chandra Piyush Madan Kush R. Varshney Murray Campbell Moninder Singh F. Rossi AI4CE 11 23 0 21 Sep 2018
Incorporating Behavioral Constraints in Online AI Systems Avinash Balakrishnan Djallel Bouneffouf Nicholas Mattei F. Rossi OffRL 36 66 0 15 Sep 2018
Combining imagination and heuristics to learn strategies that generalize Erik J Peterson Necati Alp Muyesser Timothy D. Verstynen Kyle Dunovan 6 0 0 10 Sep 2018
Reinforcement Learning under Threats Víctor Gallego Roi Naveiro D. Insua AAML 21 25 0 05 Sep 2018
A Roadmap for Robust End-to-End Alignment L. Hoang 28 1 0 04 Sep 2018
RuleMatrix: Visualizing and Understanding Classifiers with Rules Yao Ming Huamin Qu E. Bertini FAtt 20 214 0 17 Jul 2018
Modeling Friends and Foes Pedro A. Ortega Shane Legg AAML 8 3 0 30 Jun 2018
Penalizing side effects using stepwise relative reachability Victoria Krakovna Laurent Orseau Ramana Kumar Miljan Martic Shane Legg 20 55 0 04 Jun 2018
Virtuously Safe Reinforcement Learning Henrik Aslund El-Mahdi El-Mhamdi R. Guerraoui Alexandre Maurer 14 5 0 29 May 2018
Reward Constrained Policy Optimization Chen Tessler D. Mankowitz Shie Mannor 11 536 0 28 May 2018
A Lyapunov-based Approach to Safe Reinforcement Learning Yinlam Chow Ofir Nachum Edgar A. Duénez-Guzmán Mohammad Ghavamzadeh 14 500 0 20 May 2018
AGI Safety Literature Review Tom Everitt G. Lea Marcus Hutter AI4CE 36 115 0 03 May 2018
Learning model-based strategies in simple environments with hierarchical q-networks Necati Alp Muyesser Kyle Dunovan Timothy D. Verstynen 21 1 0 20 Jan 2018
Índifference' methods for managing agent rewards Stuart Armstrong Xavier O'Rourke 11 19 0 18 Dec 2017
Occam's razor is insufficient to infer the preferences of irrational agents Stuart Armstrong Sören Mindermann 19 92 0 15 Dec 2017
Good and safe uses of AI Oracles Stuart Armstrong Xavier O'Rorke 32 26 0 15 Nov 2017
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 933 0 21 Oct 2016
Safe Exploration in Markov Decision Processes T. Moldovan Pieter Abbeel 78 308 0 22 May 2012