Steve Hanks
- Artificial Intelligence top 0.5%
- AI-based Problem Solving and Planning 20
- Logic, Reasoning, and Knowledge 17
- Bayesian Modeling and Causal Inference 9
- Semantic Web and Ontologies 5
- Multi-Agent Systems and Negotiation 3
- Software top 5%
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- Optimization and Search Problems 3
- Caching and Content Delivery 2
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- Complex Systems and Decision Making 2
- Co-authors
- Craig BoutilierDrew McDermottTaraneh DeanDaniel S. WeldOmid MadaniAnne CondonNicholas KushmerickDenise L. Draper
- Journals
- Artificial Intelligence (4 papers)Journal of Artificial Intelligence Research (2 papers)SIAM Journal on Computing (1 paper)
- Partner nations
- United StatesCanadaAustralia
In The Last Decade
Steve Hanks
28 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 2.0k
- Software 83
- Computer Networks and Communications 487
- Computational Theory and Mathematics 327
- Management Science and Operations Research 206
Countries citing papers authored by Steve Hanks
This map shows the geographic impact of Steve Hanks'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 Steve Hanks with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve Hanks more than expected).
Fields of papers citing papers by Steve Hanks
This network shows the impact of papers produced by Steve Hanks. 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 Steve Hanks. The network helps show where Steve Hanks may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Steve Hanks, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Broad vs Narrow: Modelling Strategies for Online Behavioural Targeting | 2011 | 1 |
| 2 | Proceedings of the Fifth International Workshop on Data Mining and Audience Intelligence for Advertising (ADKDD) | 2011 | 6 |
| 3 | 2003 | 123 | |
| 4 | On the undecidability of probabilistic planning and infinite-horizon partially observable Markov decision problems | 1999 | 128 |
| 5 | Planning under uncertainty: structural assumptions and computational leverage | 1996 | 68 |
| 6 | Efficient Information Gathering on the Internet (Extended Abstract) | 1996 | 1 |
| 7 | Flaw selection strategies for value-directed planning | 1996 | 19 |
| 8 | 1995 | 193 | |
| 9 | An algorithm for probabilistic least-commitment planning | 1994 | 54 |
| 10 | Optimal planning with a goal-directed utility model | 1994 | 43 |
| 11 | Probabilistic planning with information gathering and contingent execution | 1994 | 127 |
| 12 | Utility-directed planning | 1994 | 2 |
| 13 | Exploiting domain structure to achieve efficient temporal reasoning | 1993 | 5 |
| 14 | 1993 | 100 | |
| 15 | Representations for Decision-Theoretic Planning: Utility Functions for Deadline Goals. | 1992 | 42 |
| 16 | An Approach to Planning with Incomplete Information. | 1992 | 126 |
| 17 | Practical temporal projection | 1990 | 31 |
| 18 | Representing and computing temporally scoped beliefs | 1988 | 6 |
| 19 | Default reasoning, nonmonotonic logics, and the frame problem | 1986 | 135 |
| 20 | Temporal Reasoning and Default Logics. | 1985 | 14 |
About Steve Hanks
Steve Hanks is a scholar working on Artificial Intelligence, Software and Computer Networks and Communications, having authored 28 papers that have together received 2.3k indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (20 papers), Logic, Reasoning, and Knowledge (17 papers), Bayesian Modeling and Causal Inference (9 papers), Semantic Web and Ontologies (5 papers), Optimization and Search Problems (3 papers), Multi-Agent Systems and Negotiation (3 papers), Complex Systems and Decision Making (2 papers) and Caching and Content Delivery (2 papers). The work is most often cited by research in Artificial Intelligence (2.0k citations), Software (83 citations) and Computer Networks and Communications (487 citations). Steve Hanks has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Craig Boutilier, Drew McDermott, Taraneh Dean, Daniel S. Weld, Omid Madani, Anne Condon, Nicholas Kushmerick, Denise L. Draper, Michael P. Williamson and Peter Haddawy. Their work appears in journals such as Artificial Intelligence, Journal of Artificial Intelligence Research, SIAM Journal on Computing, AI Magazine and Computational Intelligence.
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.