UGM Workshop Series on
Explainable and Sustainable AI 2025
Shaping the Future of AI: A New Approach to AI based on Interaction Space Theory
Yogyakarta, 20-24 October 2025
Embedded Files
About
About
As AI applications rapidly expand, the demand for systems that are transparent, explainable, and sustainable has become critical. Conventional models often function as "black boxes," raising concerns about fairness, accountability, and reliability. IS theory offers a rigorous yet intuitive framework to design AI systems that can be explained, audited, and responsibly adapted.
Speaker
Speaker
Dr. Paolo Giordano is a senior researcher at the University of Vienna . He is the initiator of the development of a novel approach to artificial intelligence (AI) based on interaction spaces (IS) theory, a new mathematical theory of complex systems (CS).
Topics
Topics
Definition of Interaction Space
Clock functions and embedding theorem
Fuzzy logic based indicators
Review: mathematical definition of complex systems, of complex adaptive systems and examples
Review: cause-effect preserving functors; simultaneous interactions
Open research project: Introduction to our ideas for ARC-AGI
Open research project: Introduction to pattern recognition in discrete systems using interaction spaces: “Recognise when two objects are equal or not”
Registration Fee
Registration Fee
Student
Undergraduate : IDR 250k
Graduate : IDR 500k
International : USD 50
General Participant
Local : IDR 750k
International : USD 75
Important Date
Important Date
Registration Open: 22nd September 2025
Registration Closed: 6th October, 2025
Payment Deadline: 10th October, 2025
Workshop: 20th-24th October 2025
Lecture notes
Lecture notes
We are pleased to inform you that the Lecture notes of the UGM Workshop Series on Explainable and Sustainable AI 2025 is now available.
You can find and download it here.
You can also find the videos of the lectures in this link.
Suggested reading
Suggested reading
Publications
Publications
Giordano, Paolo. A mathematical definition of complex adaptive system as interaction space. (https://arxiv.org/abs/2407.02181)
Giordano, Paolo. Interaction spaces: Towards a Universal Mathematical Theory of Complex Systems. (https://arxiv.org/abs/2407.02175v1)
Lecture notes
Lecture notes
Here is the list of titles of the lectures of the "Introduction to complex systems" online course by Paolo Giordano that may be related to the workshop.
Lecture 1: Introduction to the Study of Complexity, Properties Common to Complex Systems (link video 1)
Lecture 2: Core Goals Disciplines and Methodology of the science of complexity, Definitions of Complexity (link video 2)
Lecture 3, 4, 5: What are Complex Systems, Celluar automata, urban parcels (link video 3, link video 4, link video 5)
Lecture 6: Collaborative lectures, White-Engelen model (link video 6)
Lecture 7: White-Engelen model, Calibration, validation and support decisions (link video 7)
Lecture 8: Agent based models 1 (link video 8)
Lecture 9: Agent based models 2 (link video 9)
Lecture 10: Cause-effect preserving functors 1 (link video 10)
Lecture 11: Cause-effect preserving functors 2 (link video 11)
Lecture 12: Ideas for ARC-AGI 1 (link video 12)
Lecture 13: Ideas for ARC-AGI 2 (link video 13)
Lecture 14: A first definition of interaction spaces (link video 14)
Lecture 15: Mathematical definition of complex adaptive systems 1 (link video 15)
Lecture 16: Mathematical definition of complex adaptive systems 2 (link video 16)
All the lecture notes and recording are available here.
Additional Reference
Additional Reference
Chollet, F. et. all. ARC-AGI-2: A New Challenge for Frontier AI Reasoning Systems. 2025 (https://arxiv.org/abs/2505.11831v1)
Modeling Complex Systems (https://link.springer.com/book/10.1007/978-1-4419-6562-2)
Casti, J.L. Would-be worlds: Toward a theory of complex systems. Artificial Life and Robotics 1, 11–13 (1997). https://doi.org/10.1007/BF02471105
CausaLens. An Overview of the Methodologies of Causal Discovery (https://causalai.causalens.com/resources/research/an-overview-of-the-methodologies-of-causal-discovery/)
Ceccherini-Silberstein, Tullio. Michel Coornaert. Springer Monograph in Mathematics: Cellular Automata and Groups. 2010.
Dominique Chu, Roger Strand, and Ragnar Fjelland. Theories of Complexity: Common Denominators of Complex Systems. 2003
Crutchfield, James P. Between order and chaos. Macmillan Publishers Limited: Nature Physics. 2012. DOI: 10.1038/NPHYS2190
Feng, Song. et. all. Hypergraph models of biological networks to identify genes critical to pathogenic viral response. BMC Bioinformatics. https://doi.org/10.1186/s12859-021-04197-2
Grothendieck. L’importance d’être seul.
Judea Pearl, AI, and Causality: What Role do Statisticians Play? Amstat News, AI Special Issue, 555:6-9, September 2023.
Leinser, Tom. Basic Category Theory. 2014. Cambridge.
Leinser, Tom. Higher Operads, Higher Categories. http://arXiv.org/abs/math/0305049v1
Llyod, Seth. Measures of Complexity: A Nonexhaustive List. 2001. IEEE Control Systems Magazine.
Kai Nagel, Michael Schreckenberg. A cellular automaton model for freeway traffic. Journal de Physique I, EDP Sciences, 1992, 2 (12), pp.2221-2229. 10.1051/jp1:1992277. jpa- 00246697.
Lecture notes
Lecture notes
We are pleased to inform you that the Lecture notes of the UGM Workshop Series on Explainable and Sustainable AI 2025 is now available.
You can find and download it here.
You can also find the videos of the lectures in this link.
Suggested reading
Suggested reading
Publications
Publications
Giordano, Paolo. A mathematical definition of complex adaptive system as interaction space. (https://arxiv.org/abs/2407.02181)
Giordano, Paolo. Interaction spaces: Towards a Universal Mathematical Theory of Complex Systems. (https://arxiv.org/abs/2407.02175v1)
Lecture notes
Lecture notes
Here is the list of titles of the lectures of the "Introduction to complex systems" online course by Paolo Giordano that may be related to the workshop.
Lecture 1: Introduction to the Study of Complexity, Properties Common to Complex Systems (link video 1)
Lecture 2: Core Goals Disciplines and Methodology of the science of complexity, Definitions of Complexity (link video 2)
Lecture 3, 4, 5: What are Complex Systems, Celluar automata, urban parcels (link video 3, link video 4, link video 5)
Lecture 6: Collaborative lectures, White-Engelen model (link video 6)
Lecture 7: White-Engelen model, Calibration, validation and support decisions (link video 7)
Lecture 8: Agent based models 1 (link video 8)
Lecture 9: Agent based models 2 (link video 9)
Lecture 10: Cause-effect preserving functors 1 (link video 10)
Lecture 11: Cause-effect preserving functors 2 (link video 11)
Lecture 12: Ideas for ARC-AGI 1 (link video 12)
Lecture 13: Ideas for ARC-AGI 2 (link video 13)
Lecture 14: A first definition of interaction spaces (link video 14)
Lecture 15: Mathematical definition of complex adaptive systems 1 (link video 15)
Lecture 16: Mathematical definition of complex adaptive systems 2 (link video 16)
All the lecture notes and recording are available here.
Additional Reference
Additional Reference
Chollet, F. et. all. ARC-AGI-2: A New Challenge for Frontier AI Reasoning Systems. 2025 (https://arxiv.org/abs/2505.11831v1)
Modeling Complex Systems (https://link.springer.com/book/10.1007/978-1-4419-6562-2)
Casti, J.L. Would-be worlds: Toward a theory of complex systems. Artificial Life and Robotics 1, 11–13 (1997). https://doi.org/10.1007/BF02471105
CausaLens. An Overview of the Methodologies of Causal Discovery (https://causalai.causalens.com/resources/research/an-overview-of-the-methodologies-of-causal-discovery/)
Ceccherini-Silberstein, Tullio. Michel Coornaert. Springer Monograph in Mathematics: Cellular Automata and Groups. 2010.
Dominique Chu, Roger Strand, and Ragnar Fjelland. Theories of Complexity: Common Denominators of Complex Systems. 2003
Crutchfield, James P. Between order and chaos. Macmillan Publishers Limited: Nature Physics. 2012. DOI: 10.1038/NPHYS2190
Feng, Song. et. all. Hypergraph models of biological networks to identify genes critical to pathogenic viral response. BMC Bioinformatics. https://doi.org/10.1186/s12859-021-04197-2
Grothendieck. L’importance d’être seul.
Judea Pearl, AI, and Causality: What Role do Statisticians Play? Amstat News, AI Special Issue, 555:6-9, September 2023.
Leinser, Tom. Basic Category Theory. 2014. Cambridge.
Leinser, Tom. Higher Operads, Higher Categories. http://arXiv.org/abs/math/0305049v1
Llyod, Seth. Measures of Complexity: A Nonexhaustive List. 2001. IEEE Control Systems Magazine.
Kai Nagel, Michael Schreckenberg. A cellular automaton model for freeway traffic. Journal de Physique I, EDP Sciences, 1992, 2 (12), pp.2221-2229. 10.1051/jp1:1992277. jpa- 00246697.
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