Teodor C. Przymusiński

70 papers receiving 1.2k citations

Peers

Teodor C. Przymusiński
Comparison fields: 5 of 46
  • Artificial Intelligence 1.2k
  • Computational Theory and Mathematics 519
  • Geometry and Topology 249
  • Mathematical Physics 180
  • Computer Networks and Communications 142
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Countries citing papers authored by Teodor C. Przymusiński

Since Specialization
Citations

This map shows the geographic impact of Teodor C. Przymusiński'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 Teodor C. Przymusiński with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Teodor C. Przymusiński more than expected).

Fields of papers citing papers by Teodor C. Przymusiński

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Teodor C. Przymusiński. 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 Teodor C. Przymusiński. The network helps show where Teodor C. Przymusiński may publish in the future.

Co-authorship network of co-authors of Teodor C. Przymusiński

This figure shows the co-authorship network connecting the top 25 collaborators of Teodor C. Przymusiński. A scholar is included among the top collaborators of Teodor C. Przymusiński 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 Teodor C. Przymusiński. Teodor C. Przymusiński is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 66
3
Preliminary exploration on actions as updates.
9
4
Dynamic Logic Programming.
30
5 2
6 7
7 21
8
A knowledge representation framework based on autoepistemic logic of minimal beliefs
8
9
Well-Founded Completions of Logic Programs.
7
10
Autoepistemic Logics of Closed Beliefs and Logic Programming.
11
11
Extended stable semantics for normal and disjunctive programs
54
12
Three-valued formalizations of non-monotonic reasoning and logic programming
21
13
Non-Monotonic Formalisms and Logic Programming.
14
14
On the relationship between logic programming and non-monotonic reasoning
9
15
Weakly Perfect Model Semantics for Logic Programs.
45
16
Minimal Model Semantics vs. Negation as Failure: A Comparison of Semantics.
2
17
Perfect Model Semantics.
39
18
Query answering in circumscriptive and closed-world theories
11
19 6
20 2

About Teodor C. Przymusiński

Teodor C. Przymusiński is a scholar working on Geometry and Topology, Computational Theory and Mathematics and Mathematical Physics, having authored 73 papers that have together received 1.5k indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (40 papers), Advanced Algebra and Logic (27 papers) and Semantic Web and Ontologies (23 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Computational Theory and Mathematics (519 citations) and Geometry and Topology (249 citations). Teodor C. Przymusiński has collaborated with scholars based in United States, Portugal and Poland. Frequent co-authors include Halina Przymusinska, Michael Gelfond, Luı́s Moniz Pereira, José Júlio Alferes, João Leite, Franklin D. Tall, Hudson Turner, Jürgen Dix, Stefan Brass and Ilkka Niemelä. Their work appears in journals such as Artificial Intelligence, American Mathematical Monthly and Theoretical Computer Science.

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.

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