Towards a Theoretical Foundation of Process Science
- URL: http://arxiv.org/abs/2404.00065v1
- Date: Thu, 28 Mar 2024 08:19:39 GMT
- Title: Towards a Theoretical Foundation of Process Science
- Abstract summary: Process science is a highly interdisciplinary field of research.
Despite numerous proposals, process science lacks an adequate understanding of the core concepts of the field.
A more systematic framework to cope with process science is mandatory.
- Score: 1.4372498385359374
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Process science is a highly interdisciplinary field of research. Despite numerous proposals, process science lacks an adequate understanding of the core concepts of the field, including notions such as process, event, and system. A more systematic framework to cope with process science is mandatory. We suggest such a framework using an example. The framework itself addresses three aspects: architecture, statics, and dynamics. Corresponding formal concepts, based on established scientific theories, together provide an integrated framework for understanding processes in the world. We argue that our foundations have positive implications not only for theoretical research, but also for empirical research, e.g., because hypothesized relationships can be explicitly tested. It is now time to start a discussion about the foundations of our field.
Related papers
- ECLAIR: A Causally-Grounded AI Framework for Scientific Discovery in Empirical Software Engineering [51.19819833971252]
This paper introduces ECLAIR, a causally grounded AI framework that integrates Large Language Models into every stage of the scientific process.<n>ECLAIR treats LLMs as active scientific agents operating under the principles of causal inference.
arXiv Detail & Related papers (2026-08-03T14:47:03Z) - Theoretical adversarial collaboration: a template [0.0]
We propose a five-step template for conducting theoretical adversarial collaborations.<n>The procedure is designed to move disputants beyond familiar critique-reply-rejoinder exchanges.<n>The template was developed through reflection on, and implemented in, our own adversarial collaboration in philosophy and foundations of physics.
arXiv Detail & Related papers (2026-07-17T15:17:37Z) - From Observation to Insight: Mechanistic World Models and the Quest for Autonomous Discovery [60.11725132433485]
We argue that scientific discovery is fundamentally a problem of knowledge organisation.<n>We introduce Mechanistic World Models, a new design paradigm that places reusable mechanisms at the centre of representation, computation and learning.
arXiv Detail & Related papers (2026-07-14T08:03:27Z) - What is 'undone computer science'? [0.0]
'undone science' refers to research questions that are neglected, ignored, or left unfunded.<n>This issue examines whether the way computer science is structured makes it possible to identify and ethical questions that are crucial for its development and conception.
arXiv Detail & Related papers (2026-05-25T17:48:12Z) - There Will Be a Scientific Theory of Deep Learning [62.690977616250954]
We make the case that a scientific theory of deep learning is emerging.<n>We identify five growing bodies of work that point toward such a theory.<n>We argue that the emerging theory is best thought of as a mechanics of the learning process.
arXiv Detail & Related papers (2026-04-23T13:58:12Z) - The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap [0.2538209532048867]
We argue that science follows the steepest local gradient of tractability, empirical accessibility, and institutional reward.<n>We identify three interlocking mechanisms of lock-in-cognitive, formal, and institutional--and argue that recognizing these mechanisms is a prerequisite for designing meta-scientific strategies capable of escaping local optima.
arXiv Detail & Related papers (2026-04-11T17:09:43Z) - Realism and Ontology in Quantum Mechanics and String Theory [0.0]
Dualities in physics have challenged traditional forms of scientific realism.<n>We argue that ontological commitment should be treated as tied to specific empirical contexts.<n>We show how our view accommodates ontological pluralism while preserving a robust form of structural realism.
arXiv Detail & Related papers (2025-12-18T23:31:13Z) - PRISM-Physics: Causal DAG-Based Process Evaluation for Physics Reasoning [57.868248683256574]
PRISM-Physics is a process-level evaluation framework and benchmark for complex physics reasoning problems.<n> Solutions are represented as directed acyclic graphs (DAGs) of formulas.<n>Results show that our evaluation framework is aligned with human experts' scoring.
arXiv Detail & Related papers (2025-10-03T17:09:03Z) - Demystifying Scientific Problem-Solving in LLMs by Probing Knowledge and Reasoning [53.82037883518254]
We introduce SciReas, a diverse suite of existing benchmarks for scientific reasoning tasks.<n>We then propose KRUX, a probing framework for studying the distinct roles of reasoning and knowledge in scientific tasks.
arXiv Detail & Related papers (2025-08-26T17:04:23Z) - Towards a Large Physics Benchmark [1.882115594816394]
We introduce a benchmark framework to evaluate, monitor and steer large language model development in fundamental physics.<n>We develop a scoring system in which each question is scored by an expert for its correctness, difficulty, and surprise.<n>Our current dataset contains diverse set of examples, including a machine learning challenge to classify high-energy physics events.
arXiv Detail & Related papers (2025-07-29T11:19:00Z) - Can Theoretical Physics Research Benefit from Language Agents? [50.57057488167844]
Large Language Models (LLMs) are rapidly advancing across diverse domains, yet their application in theoretical physics research is not yet mature.<n>This position paper argues that LLM agents can potentially help accelerate theoretical, computational, and applied physics when properly integrated with domain knowledge and toolbox.<n>We envision future physics-specialized LLMs that could handle multimodal data, propose testable hypotheses, and design experiments.
arXiv Detail & Related papers (2025-06-06T16:20:06Z) - A Theory-driven Interpretation and Elaboration of Verification and Validation [49.97673761305336]
This paper presents a formal theory of verification and validation (V&V) within systems engineering.<n>We develop precise definitions of verification and validation, articulating their roles in confirming and contextualizing knowledge about systems.
arXiv Detail & Related papers (2025-04-11T17:58:07Z) - Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning [51.11965014462375]
Multimodal Large Language Models (MLLMs) integrate text, images, and other modalities.
This paper argues that MLLMs can significantly advance scientific reasoning across disciplines such as mathematics, physics, chemistry, and biology.
arXiv Detail & Related papers (2025-02-05T04:05:27Z) - Theory building for empirical software engineering in qualitative research: Operationalization [4.268591926288843]
This paper presents a set of procedures to systematize the operationalization phase in theory building.
We operationalize the concepts and propositions that make up our theory to generate constructs and empirically testable hypotheses.
arXiv Detail & Related papers (2024-12-03T11:15:27Z) - Ontology of Belief Diversity: A Community-Based Epistemological Approach [44.99833362998488]
We focus on developing a pragmatic ontology of belief systems, which is a complex and often controversial space.
By iterating on our community-based design until mutual agreement is reached, we found that methods were best for categorizing the fundamental ways beliefs differ.
arXiv Detail & Related papers (2024-07-25T09:02:50Z) - Ontology-Driven Processing of Transdisciplinary Domain Knowledge [15.819087559924784]
Modern science is unable to solve real-world problems in a fundamental way.
Noosphere thesis appeals to the scientific worldview that needs to be built in a way that overcomes the interdisciplinary barriers.
arXiv Detail & Related papers (2023-11-01T07:42:34Z) - Getting aligned on representational alignment [93.08284685325674]
We study the study of representational alignment in cognitive science, neuroscience, and machine learning.
Despite their overlapping interests, there is limited knowledge transfer between these fields.
We propose a unifying framework that can serve as a common language for research on representational alignment.
arXiv Detail & Related papers (2023-10-18T17:47:58Z) - Ontology for Conceptual Modeling: Reality of What Thinging Machines Talk
About, e.g., Information [0.0]
This paper develops an interdisciplinary research approach to develop a diagrammatic-based on the foundation for conceptual modeling (CM)
It is an endeavor to escape an offshore procurement of ontology from philosophy and implant it in CM.
The results seem to indicate a promising approach to define information and understand its nature.
arXiv Detail & Related papers (2023-08-16T03:21:27Z) - Promoting the transition to quantum thinking: development of a secondary
school course for addressing knowledge revision, organization, and
epistemological challenges [0.0]
We describe the development of a course of quantum mechanics for secondary school designed to address the challenges related to the revision of classical knowledge.
The course is based on a systemic approach to conceptual change, which relies on its analysis in the transition from classical to quantum mechanics.
arXiv Detail & Related papers (2022-12-31T16:09:37Z) - Revise and Resubmit: An Intertextual Model of Text-based Collaboration
in Peer Review [52.359007622096684]
Peer review is a key component of the publishing process in most fields of science.
Existing NLP studies focus on the analysis of individual texts.
editorial assistance often requires modeling interactions between pairs of texts.
arXiv Detail & Related papers (2022-04-22T16:39:38Z) - Computational Argumentation and Cognition [0.3867363075280543]
This paper stems from the 1st Workshop on Computational Argumentation and Cognition (COGNITAR)
It argues that within the context of Human-Centric AI the use of theory and methods from Computational Argumentation for the study of Cognition can be a promising avenue to pursue.
The paper presents the main problems and challenges in the area that would need to be addressed, both at the scientific level but also at the level of synthesis of ideas and approaches from the various disciplines involved.
arXiv Detail & Related papers (2021-11-12T21:44:30Z) - Quantum realism: axiomatization and quantification [77.34726150561087]
We build an axiomatization for quantum realism -- a notion of realism compatible with quantum theory.
We explicitly construct some classes of entropic quantifiers that are shown to satisfy almost all of the proposed axioms.
arXiv Detail & Related papers (2021-10-10T18:08:42Z) - Scientia Potentia Est -- On the Role of Knowledge in Computational
Argumentation [52.903665881174845]
We propose a pyramid of types of knowledge required in computational argumentation.
We briefly discuss the state of the art on the role and integration of these types in the field.
arXiv Detail & Related papers (2021-07-01T08:12:41Z) - The General Theory of General Intelligence: A Pragmatic Patternist
Perspective [0.0]
Review covers underlying philosophies, formalizations of the concept of intelligence, and a proposed high level architecture for AGI systems.
The specifics of human-like cognitive architecture are presented as manifestations of these general principles.
Lessons for practical implementation of advanced AGI in frameworks such as OpenCog Hyperon are briefly considered.
arXiv Detail & Related papers (2021-03-28T10:11:25Z) - Formalising Concepts as Grounded Abstractions [68.24080871981869]
This report shows how representation learning can be used to induce concepts from raw data.
The main technical goal of this report is to show how techniques from representation learning can be married with a lattice-theoretic formulation of conceptual spaces.
arXiv Detail & Related papers (2021-01-13T15:22:01Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.