2023
70) Polkowski. Lech: Logic: Reference Book for Computer Scientists - The 2nd Revised, Modified, and Enlarged Edition of "Logics for Computer and Data Sciences, and Artificial Intelligence". Intelligent Systems Reference Library 245, Springer 2023, ISBN 978-3-031-42033-7, pp. 1-450
2022
69) Polkowski, Lech. (2022). Logics for Computer and Data Sciences, and Artificial Intelligence. 10.1007/978-3-030-91680-0.
2020
68) Polkowski, Lech. ‘On the Compactness Property of Mereological Spaces’. Fundam. Inform. 172(1): 73-95 (2020)
67) Krzysztof Ropiak, Lech Polkowski, Piotr Artiemjew: Proceedings of the 28th International Workshop on Concurrency, Specification and Programming, Olsztyn, Poland, September 24-26th, 2019. CEUR Workshop Proceedings 2571, CEUR-WS.org 2020
2019
66) Lech Polkowski,: ‘Introducing Mass-based Rough Mereology in a Mereological Universe with Relations to Fuzzy Logics and a Generalization of the Łukasiewicz Logical Foundations of Probability’. Fundam. Inform. 166(3): 227-249 (2019)
65) Lech Polkowski: Jan Łukasiewicz Life, Work, Legacy - On the Centenary of the Farewell Lecture at Warsaw University During Which Jan Łukasiewicz Introduced Multi-valued Logic and on His 140th Birth Anniversary in the Year of 100th Anniversary of Regained Polish Independence. Trans. Rough Sets 21: 1-47 (2019)
64) Lech Polkowski: A Logic for Spatial Reasoning in the Framework of Rough Mereology. In: Peters J., Skowron A. (eds) Transactions on Rough Sets XXI. Lecture Notes in Computer Science, vol 10810. Springer, Berlin, Heidelberg
63) Lech Polkowski: On logical and mereological renderings of the Bayes theorem. CS&P 2019
2018
62) Lech Polkowski:: The Bayes Theorem Counterpart in Mass-Based Rough Mereology. CS&P 2018
61) Lech Polkowski, Lukasz Zmudzinski, Piotr Artiemjew: Robot Navigation and Path Planning by Means of Rough Mereology. IRC 2018: 363-368
60) Wojciech Budzisz, Lech T. Polkowski: Introducing Dynamic Structures of Rough Sets. The Case of Text Processing: Anaphoric Co-reference in Texts in Natural Language. IJCSR 2018: 455-463
2017
59) Andrzej W. Przybyszewski, Lech T. Polkowski: Theory of Mind and Empathy. Part I - Model of Social Emotional Thinking. Fundam. Inform. 150(2): 221-230 (2017)
58) Lech T. Polkowski: From Leśniewski, Łukasiewicz, Tarski to Pawlak: Enriching Rough Set Based Data Analysis. A Retrospective Survey. Fundam. Inform. 154(1-4): 343-358 (2017)
57) Lech Polkowski: On Mereology as a Tool in Problems of Intelligent Control, Granular Computing, Data Analysis and Approximate and Spatial Reasoning. IJCRS (2) 2017: 108-129 (2017)
56) Lech Polkowski, Yiyu Yao, Piotr Artiemjew, Davide Ciucci, Dun Liu, Dominik Slezak, Beata Zielosko: Rough Sets - International Joint Conference, IJCRS 2017, Olsztyn, Poland, July 3-7, 2017, Proceedings, Part I. Lecture Notes in Computer Science 10313, Springer 2017, ISBN 978-3-319-60836-5 2017
55) Lech Polkowski, Yiyu Yao, Piotr Artiemjew, Davide Ciucci, Dun Liu, Dominik Slezak, Beata Zielosko: Rough Sets - International Joint Conference, IJCRS 2017, Olsztyn, Poland, July 3-7, 2017, Proceedings, Part II. Lecture Notes in Computer Science 10314, Springer 2017, ISBN 978-3-319-60839-6 (2017)
2016
54) Lech Polkowski: Rough sets of Zdzislaw Pawlak give new life to old concepts. IJCRS2016, Santiago de Chile (2016)
53) Lech Polkowski: Mereology and Uncertainty. Logic and Logical Philosophy 24(4):449-468 (2016)
52) Piotr Artiemjew, Bartosz Nowak, Lech Polkowski: A new classifier based on the dual indiscernibility matrix. ICIST 2016, 380-391 (2016)
51) LechT.Polkowski, Bartosz A. Nowak: Betweenness, Łukasiewicz Rough Inclusions, Euclidean Representations in Information Systems, Hyper–granules and Conflict Resolution. Fundam. Inf.: vol.147, no 2-3 (2016).
50) Lech Polkowski:, Piotr Artiemjew: Granular Computing in Decision Approximation. ISRL vol. 77, Springer International publishing Switzerland, Cham (2015)
49) Lech Polkowski, Maria Semeniuk-Polkowska: Where Rough Sets and Fuzzy Sets Meet. Fundam. Inform. 142(1-4): 269-284 (2015)
48) Lech Polkowski: Mereology in Engineering and Computer Science. In Calosi, C., Graziani, P. (eds.): Mereology and the Sciences. Springer Synthese Library vol. 371, 217-292, 2015
47) Lech Polkowski, Maria Semeniuk-Polkowska: Boundaries, Borders, Fences, Hedges. Fundam. Inform. 129(1-2): 149-159 (2014)
46)Lech Polkowski, Maria Semeniuk-Polkowska: On the Problem of Boundaries from Mereology and Rough Mereology Points of View. Fundam. Inform. 133(2-3): 241-255 (2014)
45) Maria Semeniuk-Polkowska, Lech Polkowski: On a Notion of Extensionality for Artifacts. Fundam. Inform. 127(1-4): 65-80 (2013)
44) Lech Polkowski: Approximate Reasoning by Parts. An Introduction to Rough Mereology. ISRL vol. 20, Springer Verlag, Berlin-Heidelberg (2011)
43) Lech Polkowski, Piotr Artiemjew: Granular computing in the frame of rough mereology. A case study: Classification of data into decision categories by means of granular reflections of data. Int. J. Intell. Syst. 26(6): 555-571 (2011)
43) Lech Polkowski, Pawel Osmialowski: Navigation for mobile autonomous robots and their formations: An application of spatial reasoning induced from rough mereological geometry. In: Barrera, A. (ed.): Mobile Robots Navigation
42)Lech Polkowski, Maria Semeniuk-Polkowska: Granular Rough Mereological Logics with Applications to Dependencies in Information and Decision Systems. LNCS. Trans. Rough Sets 12: 1-20(2010)
41) Paweł Osmialowski, Lech Polkowski: Spatial Reasoning Based on Rough Mereology: A Notion of a Robot Formation and Path Planning Problem for Formations of Mobile Autonomous Robots. LNCS. Trans. Rough Sets 12: 143-169 (2010)
40) Lech Polkowski: Data Mining and Knowledge Discovery: Case based reasoning, nearest neighbor and rough sets. In: Meyers R. A. (ed.): Encyclopedia of Complexity and Systems Sciences, Article 00 391, Springer Verlag, Berlin (2009)
39) Lech Polkowski: Granulation of Knowledge : Similarity based approach in Information and decision systems. In: Meyers, R. A. (ed.): Encyclopedia of Complexity and Systems Sciences, Article 00 788, Springer Verlag, Berlin (2009)
38) Lech Polkowski, Piotr Artiemjew: On Knowledge Granulation and Applications to Classifier Induction in the Framework of Rough Mereology. Int. J. Computational Intelligence Systems 2(4): 315-331 (2009)
37) Lech Polkowski, Pawel Osmialowski: Spatial reasoning with applications to mobile robotics. In: Xing-Jian, J. (ed.): Mobile Robots Motion Planning. New Challenges. I-Tech, Vienna, 433-453 (2008)
36) Lech Polkowski: Unified approach to granulation of knowledge and granular computing based on rough mereology: A survey. In: Pedrycz, W., Skowron, A., Kreinovich, V. (eds.): Handbook of Granular Computing, Chapter 16. John Wiley and Sons Ltd., Chichester (2008)
35) Lech Polkowski: On the idea of using granular rough mereological structures in classification of data. LNAI vol. 5009, 213-220, Springer Verlag, Heidelberg (2008)
34) Lech Polkowski, Maria Semeniuk-Polkowska: On Foundations and Applications of the Paradigm of Granular Rough Computing. IJCINI 2(2): 80-94 (2008)
33)Lech Polkowski: Mereological Theories of Concepts in Granular Computing. Trans. Computational Science 2: 30-45 (2008)
32) Lech Polkowski, Piotr Artiemjew: A Study in Granular Computing: On Classifiers Induced from Granular Reflections of Data. Trans. Rough Sets 9: 230-263 (2008)
31) Lech Polkowski, Piotr Artiemjew: On Classifying Mappings Induced by Granular Structures. Trans. Rough Sets 9: 264-286 (2008)
30) Lech Polkowski, Piotr Artiemjew: On granular rough computing with missing values. In: LNAI vol. 4585, 271-279, Springer Verlag, Heidelberg (2007)
29) Lech Polkowski: Concept Approximation in Mathematics and Computer Science. An Essay in Homage to Zdzislsaw Pawlak. Fundam. Inform. 75(1-4): 435-451 (2007)
28) Lech Polkowski: A model for granular computing with applications (a feature talk). In: Proceedings IEEE Conference on Granular Computing GrC2006: 9-16. Georgia Tech., Atlanta GA (2006)
27) Mariusz Flasinski, Edward Nawarecki, Lech Polkowski, Robert Schaefer, Jerzy Stefanowski, Zbigniew Suraj: Preface. Fundam. Inform. 71(1) (2006)
26) Lech Polkowski: A Set Theory for Rough Sets. Toward A Formal Calculus of Vague Statements. Fundam. Inform. 71(1): 49-61 (2006)
25) Lech Polkowski: Formal granular calculi based on rough inclusions (a feature talk). In: Proceedings IEEE 2005 Conference on Granular Computing GrC 2005: 57-62. Beijing, Tsinghua Univ. (2005)
24) Lech Polkowski, Maria Semeniuk-Polkowska: On Rough Set Logics Based on Similarity Relations. Fundam. Inform. 64(1-4): 379-390 (2005)
23) Lech Polkowski: Rough-fuzzy-neurocomputing based on rough mereological calculus of granules. Int. J. Hybrid Intell. Syst. 2(2): 91-108 (2005)
22) Sankar Kumar Pal, Lech Polkowski, Andrzej Skowron (eds.): Rough-Neural Computing. Springer Verlag, Berlin-Heidelberg (2004)
21) Guoyin Wang, Qing Liu, Tsau Young Lin, Yiyu Yao, Lech Polkowski: Preface. Fundam. Inform. 59(2-3) (2004)
20)Lech Polkowski, Maria Semeniuk-Polkowska: Some Remarks on Sets of Communicating Sequential Processes in Topological Rough Set Framework. Fundam. Inform. 60(1-4): 291-305(2004)
19) Lech Polkowski: A Note on 3-valued Rough Logic Accepting Decision Rules. Fundam. Inform. 61(1): 37-45 (2004)
18) Peter Apostoli, Akira Kanda, Lech Polkowski: First Steps Towards Computably-Infinite Information Systems. : 151-188 (2004)
17) Lech Polkowski: Rough Mereology as a Link Between Rough and Fuzzy Set Theories. A Survey. : 253-277 (2004)
16) Lech Polkowski, Boleslaw Araszkiewicz: A Rough Set Approach to Estimating the Game Value and the Shapley Value from Data. Electr. Notes Theor. Comput. Sci. 82(4): 219-227(2003)
15) Lech Polkowski: Rough Mereology: A Rough Set Paradigm for Unifying Rough Set Theory and Fuzzy Set Theory. Fundam. Inform. 54(1): 67-88 (2003)
14) Lech Polkowski: Rough Sets. Mathematical Foundations. Springer/Physica Verlag, Heidelberg (2002)
13) Lech Polkowski: On Fractal Dimension in Information Systems. Toward Exact Sets in Infinite Information Systems. Fundam. Inform. 50(3-4): 305-314 (2002)
12) Lech Polkowski, Boleslaw Araszkiewicz: A Rough Set Approach to Estimating the Game Value and the Shapley Value from Data . Fundam. Inform. 53(3-4): 335-343 (2002)
11) Lech Polkowski, Andrzej Skowron: Rough Mereological Calculi of Granules: A Rough Set Approach to Computation. Computational Intelligence 17(3): 472-492 (2001)
10) Lech Polkowski: On Connection Synthesis via Rough Mereology. Fundam. Inform. 46(1-2): 83-96 (2001)
9) Lech Polkowski, Andrzej Skowron: Rough Mereology in Information Systems with Applications to Qualitative Spatial Reasoning. Fundam. Inform. 43(1-4): 291-320 (2000)
8) Andrzej Skowron, Lech Polkowski: Rough Mereological Foundatins for Design, Analysis, Synthesis, and Control in Distributed Systems. Inf. Sci. 104(1-2): 129-156 (1998)
7) Andrzej Skowron, Lech Polkowski: Decision Algorithms: A Survey of Rough Set - Theoretic Methods. Fundam. Inform. 30(3/4): 345-358 (1997)
6)Gheorghe Paun, Lech Polkowski, Andrzej Skowron: Rough Set Approximations of Languages. Fundam. Inform. 32(2): 149-162 (1997)
5) Henryk Jan Komorowski, Lech Polkowski, Andrzej Skowron: Towards a Rough Mereology-Based Logic for Approximate Solution Synthesis. Part 1. Studia Logica 58(1): 143-184 (1997)
4) Andrzej Skowron, Lech Polkowski: Analytical Morphology: Mathematical Morphology of Decision Tables. Fundam. Inform. 27(2/3): 255-271 (1996)
3) Gheorghe Paun, Lech Polkowski, Andrzej Skowron: Parallel Communicating Grammar Systems with Negotiation. Fundam. Inform. 28(3-4): 315-330 (1996)
2) Lech Polkowski, Andrzej Skowron: Adaptive Decision-Making by Systems of Cooperating Intelligent Agents Organized on Rough Mereological Principles. Intelligent Automation & Soft Computing 2(2): 121-132 (1996)
1) Lech Polkowski, Andrzej Skowron: Rough mereology: A new paradigm for approximate reasoning. Int. J. Approx. Reasoning 15(4): 333-365 (1996)
International Joint Conference on Rough Sets 2017.
3-7 JULY 2017 OLSZTYN, POLAND. http://ijcrs2017.uwm.edu.pl
IJCRS 2017 aims at unification of many facets of Rough Set Theory from theoretical aspects of the rough set idea bordering on theory of concepts and going through algebraic structures, topological structures, logics for uncertain reasoning, decision algorithms, relations to other theories of vagueness and ambiguity, then to extensions of the rough set idea like granular structures, rough mereology, and to applications of the idea in diverse fields of applied science including hybrid methods like Rough-Fuzzy, Neuro-Rough, Neuro-Rough-Fuzzy computing.