Abhaya Nayak
- Artificial Intelligence top 5%
- Logic, Reasoning, and Knowledge 31
- Multi-Agent Systems and Negotiation 15
- Bayesian Modeling and Causal Inference 13
- Semantic Web and Ontologies 12
- AI-based Problem Solving and Planning 7
- Topic Modeling 5
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- Advanced Algebra and Logic 6
- Philosophy top 10%
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- Biomedical Text Mining and Ontologies 4
Abhaya Nayak
49 papers receiving 384 citations
Peers
Comparison fields: 5 of 77
- Artificial Intelligence 335
- General Psychology 8
- History and Philosophy of Science 26
- Computational Theory and Mathematics 79
- Philosophy 30
Countries citing papers authored by Abhaya Nayak
This map shows the geographic impact of Abhaya Nayak'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 Abhaya Nayak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Abhaya Nayak more than expected).
Fields of papers citing papers by Abhaya Nayak
This network shows the impact of papers produced by Abhaya Nayak. 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 Abhaya Nayak. The network helps show where Abhaya Nayak may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Abhaya Nayak, 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 | 2019 | 6 | |
| 2 | 2019 | 11 | |
| 3 | 2019 | 2 | |
| 4 | Probabilistic belief contraction using argumentation | 2015 | 1 |
| 5 | Iterated belief contraction from first principles | 2007 | 9 |
| 6 | DASMAS: dialogue based automation of semantic interoperability in multi agent systems | 2005 | 7 |
| 7 | Conservative belief revision | 2004 | 1 |
| 8 | Conservative belief change | 2004 | 1 |
| 9 | Coherence of laws | 2003 | 1 |
| 10 | 2003 | 72 | |
| 11 | 2002 | 2 | |
| 12 | Preferential Semantics for Causal Systems | 1999 | 5 |
| 13 | Diagrammatic Proofs | 1999 | 3 |
| 14 | Coherence Measure based on Average Use of Formulas | 1998 | 1 |
| 15 | 1997 | 1 | |
| 16 | Learning From Conditionals: Judy Benjamin's Other Problems. | 1996 | 5 |
| 17 | Changing conditional beliefs unconditionally | 1996 | 17 |
| 18 | 1996 | 10 | |
| 19 | 1994 | 25 | |
| 20 | Studies in belief change | 1993 | 5 |
About Abhaya Nayak
Abhaya Nayak is a scholar working on Artificial Intelligence, History and Philosophy of Science and Computational Theory and Mathematics, having authored 52 papers that have together received 421 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (31 papers), Multi-Agent Systems and Negotiation (15 papers), Bayesian Modeling and Causal Inference (13 papers), Semantic Web and Ontologies (12 papers), AI-based Problem Solving and Planning (7 papers), Advanced Algebra and Logic (6 papers), Topic Modeling (5 papers) and Biomedical Text Mining and Ontologies (4 papers). The work is most often cited by research in Artificial Intelligence (335 citations), General Psychology (8 citations) and History and Philosophy of Science (26 citations). Abhaya Nayak has collaborated with scholars based in Australia, Canada and Japan. Frequent co-authors include Maurice Pagnucco, Pavlos Peppas, Alok K. Sharma, Norman Foo, Mehmet A. Orgun, Mark Dras, Geoff James, Alok Sharma, Abdul Sattar and Paul E. Nelson. Their work appears in journals such as IEEE Access, Artificial Intelligence and Philosophy and Phenomenological Research.
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.