Article

Eligibility Traces for Off-Policy Policy Evaluation

Authors:

Doina Precup,

Richard S. Sutton,

Satinder P. SinghAuthors Info & Claims

ICML '00: Proceedings of the Seventeenth International Conference on Machine Learning

Pages 759 - 766

Published: 29 June 2000 Publication History

Abstract

No abstract available.

Cited By

View all

Tang SWiens JOh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Counterfactual-augmented importance sampling for semi-offline policy evaluationProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666626(11394-11429)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.5555/3666122.3666626
Rothfuss JSukhija BBirchler TKassraie PKrause AEvans RShpitser I(2023)Hallucinated adversarial control for conservative offline policy evaluationProceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence10.5555/3625834.3626000(1774-1784)Online publication date: 31-Jul-2023
https://dl.acm.org/doi/10.5555/3625834.3626000
Wu RUehara MSun WKrause ABrunskill ECho KEngelhardt BSabato SScarlett J(2023)Distributional offline policy evaluation with predictive error guaranteesProceedings of the 40th International Conference on Machine Learning10.5555/3618408.3619978(37685-37712)Online publication date: 23-Jul-2023
https://dl.acm.org/doi/10.5555/3618408.3619978
Show More Cited By

Index Terms

Eligibility Traces for Off-Policy Policy Evaluation
1. Computing methodologies
  1. Machine learning
2. Mathematics of computing
  1. Probability and statistics
    1. Probabilistic algorithms
    2. Probabilistic reasoning algorithms
      1. Markov-chain Monte Carlo methods
      2. Sequential Monte Carlo methods

Recommendations

Designing Fast and Scalable XACML Policy Evaluation Engines

Most prior research on policies has focused on correctness. While correctness is an important issue, the adoption of policy-based computing may be limited if the resulting systems are not implemented efficiently and thus perform poorly. To increase the ...
The Policy Machine: A novel architecture and framework for access control policy specification and enforcement

The ability to control access to sensitive data in accordance with policy is perhaps the most fundamental security requirement. Despite over four decades of security research, the limited ability for existing access control mechanisms to generically ...
Conflicts in Policy-Based Distributed Systems Management

Modern distributed systems contain a large number of objects and must be capable of evolving, without shutting down the complete system, to cater for changing requirements. There is a need for distributed, automated management agents whose behavior also ...

Comments

Information & Contributors

Information

Published In

ICML '00: Proceedings of the Seventeenth International Conference on Machine Learning

June 2000

1208 pages

ISBN:1558607072

Editor:
Pat Langley

Publisher

Morgan Kaufmann Publishers Inc.

San Francisco, CA, United States

Publication History

Published: 29 June 2000

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

86
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 24 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Tang SWiens JOh ANaumann TGloberson ASaenko KHardt MLevine S(2023)Counterfactual-augmented importance sampling for semi-offline policy evaluationProceedings of the 37th International Conference on Neural Information Processing Systems10.5555/3666122.3666626(11394-11429)Online publication date: 10-Dec-2023
https://dl.acm.org/doi/10.5555/3666122.3666626
Rothfuss JSukhija BBirchler TKassraie PKrause AEvans RShpitser I(2023)Hallucinated adversarial control for conservative offline policy evaluationProceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence10.5555/3625834.3626000(1774-1784)Online publication date: 31-Jul-2023
https://dl.acm.org/doi/10.5555/3625834.3626000
Wu RUehara MSun WKrause ABrunskill ECho KEngelhardt BSabato SScarlett J(2023)Distributional offline policy evaluation with predictive error guaranteesProceedings of the 40th International Conference on Machine Learning10.5555/3618408.3619978(37685-37712)Online publication date: 23-Jul-2023
https://dl.acm.org/doi/10.5555/3618408.3619978
Daley BWhite MAmato CMachado MKrause ABrunskill ECho KEngelhardt BSabato SScarlett J(2023)Trajectory-aware eligibility traces for off-policy reinforcement learningProceedings of the 40th International Conference on Machine Learning10.5555/3618408.3618681(6818-6835)Online publication date: 23-Jul-2023
https://dl.acm.org/doi/10.5555/3618408.3618681
Gao GJu SAusin MChi MAgmon NAn BRicci AYeoh W(2023)HOPE: Human-Centric Off-Policy Evaluation for E-Learning and HealthcareProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598804(1504-1513)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598804
Cai YZhang CZhao HZhao LBian JAgmon NAn BRicci AYeoh W(2023)Curriculum Offline Reinforcement LearningProceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems10.5555/3545946.3598767(1221-1229)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.5555/3545946.3598767
Ying CHao ZZhou XSu HYan DZhu JElkind E(2023)On the reuse bias in off-policy reinforcement learningProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence10.24963/ijcai.2023/502(4513-4521)Online publication date: 19-Aug-2023
https://dl.acm.org/doi/10.24963/ijcai.2023/502
Sadhukhan DKumar SSankule SMukherjee T(2023)t-RELOAD: A REinforcement Learning-based Recommendation for Outcome-driven ApplicationProceedings of the Third International Conference on AI-ML Systems10.1145/3639856.3639884(1-7)Online publication date: 25-Oct-2023
https://dl.acm.org/doi/10.1145/3639856.3639884
Kiyohara HUehara MNarita YShimizu NYamamoto YSaito YSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)Off-Policy Evaluation of Ranking Policies under Diverse User BehaviorProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599447(1154-1163)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599447
Gao QSchmidt SChowdhury AFeng GPeters JGenty KGrill WTurner DPajic MMitra SVenkatasubramanian NDubey AFeng LGhasemi MSprinkle J(2023)Offline Learning of Closed-Loop Deep Brain Stimulation Controllers for Parkinson Disease TreatmentProceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2023)10.1145/3576841.3585925(44-55)Online publication date: 9-May-2023
https://dl.acm.org/doi/10.1145/3576841.3585925
Show More Cited By

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Abstract

Cited By

Index Terms

Recommendations

Designing Fast and Scalable XACML Policy Evaluation Engines

The Policy Machine: A novel architecture and framework for access control policy specification and enforcement

Conflicts in Policy-Based Distributed Systems Management

Comments

Information

Published In

Publisher

Publication History

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

Get Access

Login options

Full Access

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations