Ronald Parr
About
In The Last Decade
Ronald Parr
53 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 109
- Artificial Intelligence 1.7k
- Computer Networks and Communications 453
- Management Science and Operations Research 447
- Control and Systems Engineering 440
- Computational Theory and Mathematics 393
Countries citing papers authored by Ronald Parr
This map shows the geographic impact of Ronald Parr's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ronald Parr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ronald Parr more than expected).
Fields of papers citing papers by Ronald Parr
This network shows the impact of papers produced by Ronald Parr. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ronald Parr. The network helps show where Ronald Parr may publish in the future.
Co-authorship network of co-authors of Ronald Parr
This figure shows the co-authorship network connecting the top 25 collaborators of Ronald Parr. A scholar is included among the top collaborators of Ronald Parr based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ronald Parr. Ronald Parr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Revisiting the Softmax Bellman Operator: Theoretical Properties and Practical Benefits. | 1 |
| 2 | Improving PAC Exploration Using the Median Of Means | 2 |
| 3 | Linear feature encoding for reinforcement learning | 4 |
| 4 | 31 | |
| 5 | Linear Complementarity for Regularized Policy Evaluation and Improvement | 25 |
| 6 | Multi-step multi-sensor hider-seeker games | 35 |
| 7 | Point-based policy iteration | 17 |
| 8 | Hierarchical Linear/Constant Time SLAM Using Particle Filters for Dense Maps | 35 |
| 9 | DP-SLAM: fast, robust simultaneous localization and mapping without predetermined landmarks | 220 |
| 10 | Reinforcement learning as classification: leveraging modern classifiers | 60 |
| 11 | Approximate policy iteration using large-margin classifiers | 0 |
| 12 | Coordinated Reinforcement Learning | 182 |
| 13 | Model-Free Least-Squares Policy Iteration | 48 |
| 14 | Making Rational Decisions Using Adaptive Utility Elicitation | 152 |
| 15 | Bayesian Fault Detection and Diagnosis in Dynamic Systems | 165 |
| 16 | Computing Factored Value Functions for Policies in Structured MDPs | 95 |
| 17 | Reinforcement Learning Using Approximate Belief States | 12 |
| 18 | Reinforcement Learning with Hierarchies of Machines | 343 |
| 19 | Generalized Prioritized Sweeping | 32 |
| 20 | Approximating optimal policies for partially observable stochastic domains | 98 |
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.