Peter Vamplew
About
In The Last Decade
Peter Vamplew
72 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 134
- Artificial Intelligence 1.3k
- Computer Networks and Communications 1.2k
- Signal Processing 742
- Information Systems 266
- Control and Systems Engineering 252
Countries citing papers authored by Peter Vamplew
This map shows the geographic impact of Peter Vamplew'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 Peter Vamplew with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Vamplew more than expected).
Fields of papers citing papers by Peter Vamplew
This network shows the impact of papers produced by Peter Vamplew. 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 Peter Vamplew. The network helps show where Peter Vamplew may publish in the future.
Co-authorship network of co-authors of Peter Vamplew
This figure shows the co-authorship network connecting the top 25 collaborators of Peter Vamplew. A scholar is included among the top collaborators of Peter Vamplew 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 Peter Vamplew. Peter Vamplew is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | A practical guide to multi-objective reinforcement learning and planning breakdown → | 158 |
| 3 | 10 | |
| 4 | Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario. | 2 |
| 5 | 136 | |
| 6 | 2 | |
| 7 | 32 | |
| 8 | MORL-Glue: a benchmark suite for multi-objective reinforcement learning | 5 |
| 9 | Taming the devil: A game-based approach to teaching immunology | 2 |
| 10 | AusDM 11 : Proceedings of the Ninth Australasian Data Mining Conference | 0 |
| 11 | OPTIMIZATION AND MATRIX CONSTRUCTIONS FOR CLASSIFICATION OF DATA | 1 |
| 12 | Applying clustering and ensemble clustering approaches to phishing profiling | 22 |
| 13 | Unsupervised color textured image segmentation using cluster ensembles and MRF model | 1 |
| 14 | 4 | |
| 15 | An anti-plagiarism editor for software development courses | 26 |
| 16 | Lego Mindstorms Robots as a Platform for Teaching Reinforcement Learning | 4 |
| 17 | PoD Can Mutate: A Simple Dynamic Directed Mutation Approach for Genetic Algorithms | 11 |
| 18 | Generalised Algorithms for Redirected Walking in Virtual Environments | 22 |
| 19 | Refining Search Queries From Examples Using Boolean Expressions and Latent Semantic Analysis | 1 |
| 20 | Learning Place Cells from Sonar data | 4 |
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.