Computational Modeling

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The use of computational models has been increasing in various fields such as natural and social sciences. However, its application in philosophy has been limited despite its potential to provide valuable insights into fundamental philosophical questions about knowledge, reality, and morality. This chapter aims to emphasize the background, scope, purpose, and significance of the study. It also states the methodology to be used and identifies the problem to be investigated. In addition, relevant terms will be defined to clarify the theoretical framework of the work.

1.1. Background of the Study

The computational theory of mind (CTM), also referred to as computationalism, is a group of philosophical perspectives that assert that the human mind functions as an information processing system. According to this viewpoint, cognition and consciousness can be understood as a type of computation. In the 1950s, a hypothesis emerged suggesting that thinking can be compared to computation and may even be a form of computation itself. Building upon this analogy, I believe that mental processes can be represented through computer programs using data structures. These data structures are ways in which programming languages organize and store information for efficient use. Programming languages offer various data structures like numbers, variables, strings, lists, and arrays. More advanced programming languages such as LISP or Prolog provide expanded means of representing complex information, including propositions and concepts. By translating a psychological theory about the types of representations used by the mind into a computer model, we can create analogous data structures in the program. A computer program is often described as a set of instructions, but these instructions require data structures to operate on, much like an inference requires propositions and rules of inference. Therefore, it is more accurate to describe computer programs and models as combinations of data structures and algorithms, which are effective methods expressed as finite steps of instructions. A computer-based model is a software application that is designed to imitate or replicate a scenario, either to predict future outcomes or to recreate past events.

The main question is how computer models can apply to philosophical inquiries about knowledge, reality, and morality. Some philosophical perspectives may argue that computer models have little relevance if philosophy's primary goal is to produce transcendental, a priori truths, or if it focuses on analyzing everyday concepts through language. However, I believe that there are no significant a priori truths, and that philosophy should resemble science by seeking to improve concepts rather than merely analyzing existing ones. While philosophy is not reducible to science due to its broader scope and normative aspects, a naturalistic approach, as advocated by philosophers like Aristotle, Bacon, Locke, Hume, Mill, Peirce, Quine, and others, recognizes the importance of scientific findings in addressing philosophical issues. Therefore, this approach opens up the possibility that computational models can offer a valuable methodology for philosophy. Aristotle, Bacon, Locke, Hume, Mill, Peirce, and Quine - all pursued a naturalistic approach in their philosophical work. This approach aims to understand the world and human nature in a way that is grounded in empirical observation and scientific inquiry. For example, Aristotle believed that knowledge about the world can be gained through careful observation and systematic investigation of natural phenomena. Bacon developed a method of inquiry that emphasized the importance of empirical evidence and experimentation in the pursuit of knowledge. Locke argued that all knowledge is derived from experience and that the mind is a tabula rasa, or blank slate, upon which experience writes. Hume emphasized the importance of empirical evidence and argued that all knowledge is based on impressions and ideas derived from experience. Mill developed a system of logic that sought to connect empirical observation and scientific inquiry with the principles of induction and deduction. Peirce developed a theory of inquiry that emphasized the importance of experimentation and the scientific method in the pursuit of knowledge. Quine developed a naturalistic epistemology that sought to integrate empirical evidence with traditional philosophical questions about knowledge, reality, and language.

This project is motivated by the desire to encourage the utilization of computer models and the belief that these models offer valuable tools for addressing philosophical questions in various fields such as epistemology, metaphysics, ethics, and the sciences. These models can assist philosophers in examining both descriptive aspects of human thinking and normative aspects of how thinking can be improved. By incorporating computer models, philosophical methodology can expand beyond traditional methods like thought experiments and abstract reasoning. I am confident that employing computational modeling effectively will enhance philosophical research, and I view this work as my contribution to advancing this objective.

1.2. Statement of the Problem

Computer models are widely used in the natural and social sciences, yet they remain uncommon in the field of philosophy of science and philosophy as a whole. This work will discuss the valuable contributions that such models make in the sciences and show how similar benefits can be gained in the philosophy of science. The philosophy of science has traditionally relied on a limited set of formal methods such as predicate logic, set theory, and probability theory. However, there are other branches of mathematics, such as differential calculus, linear algebra, dynamic systems theory, and theory of computation, that are equally relevant to important topics in epistemology and metaphysics. By utilizing these mathematical tools in computational models, we can gain valuable insights into the development of knowledge, the understanding of the mind and reality, and importantly, demonstrate the philosophical strength and dependability of computational explanations in scientific theories.

1.3. Purpose of the Study

I hope to highlight various computational modeling techniques proffered by Paul Thagard in the philosophy of science in particular, which are also applicable in other sub-disciplines of philosophy. My goal is to portray how computational modeling in the philosophy of science can ease the understanding and carrying out of scientific inquiries. Also to demonstrate practically the philosophical superiority and reliability of parallel computational accounts of theories, and describe the similarities and differences concerning computational modeling approaches and their methodological analysis in the philosophy of science. With the advancements in technology, the use of computational models in philosophy and the sciences will undoubtedly see rapid growth. Philosophers need to embrace and contribute to this progress, both by actively participating in modeling endeavors and by offering their expertise in epistemology to the scientific community. This thematic work aims to facilitate a mutually beneficial development. Additionally, I anticipate that computational modeling in the philosophy of science will become widely accepted soon. Instead of considering modeling and computational simulations as peripheral philosophical methods, they will be integrated into philosophical works as the normative means of modeling.

1.4. Scope of the Study

The role played by logic in 20th-century philosophy, it can be argued, will be played by computational modeling in the 21st century. Over the past several decades, social epistemology and philosophy of science have been important areas in the development of computational philosophy. While computational modeling is not yet widely incorporated into standard philosophical textbooks or considered a central tool in philosophy by a significant number of philosophers, its importance is steadily increasing. The methodology has produced valuable results and valuable insights across various core areas of philosophy, leading to a substantial body of relevant publications. Moreover, the research community in computational modeling within philosophy is becoming more vibrant and productive, suggesting that the field is gradually gaining mainstream recognition. This work is devoted to discussion, and analysis, but primarily to exploring examples proffered by Paul Thagard on computer-aided or computer-instantiated modeling in his work “Computational Philosophy of Science. I hope to illustrate, entirely by example, the possibilities of using computer models as tools in philosophical research in general and the philosophy of science in particular.

1.5. Significance of the Study

Computer models are valuable tools for philosophers as they can be used to tackle philosophical issues in epistemology, metaphysics, and ethics. These models can help philosophers understand how people think and provide insights on how to improve thinking processes. By employing computer models in a similar manner to scientific applications, philosophers can expand their methodology beyond thought experiments and abstract contemplation. In formal philosophy, computer models offer a wider range of representation techniques compared to traditional logic, probability, and set theory. They take into account the significant roles of imagery, analogy, and emotion in human thinking. Computer models enable the exploration of the dynamics of inference, going beyond abstract formal relationships.

1.6. Methodology

Using an exploratory methodology, I will qualitatively describe a computational model of problem-solving and learning that has been used to simulate several kinds of scientific reasoning. I will be presenting a series of exploratory examples proffered by Paul Thagard on computer modeling, using a range of computational techniques to illuminate a variety of questions in the philosophy of science.

1.7. Definition of Terms

1.7.1. Computation

According to Britannica Encyclopedia, Computation refers to the process of performing calculations, both mathematical and non-mathematical, according to a clearly defined framework such as an algorithm. Computers, whether they are mechanical, electronic, or operated by humans in the past, are used to carry out these computations. Computer science is a prominent field that focuses on the study of computation.

1.7.2. Models

As stated in the Routledge Encyclopedia of Philosophy, various types of models serve as representations of our desired understanding, goals, or actions. For instance, scale models like model airplanes share certain structural characteristics with their real counterparts but differ in other aspects such as size and materials used. Analog models, on the other hand, are particularly valuable in scientific fields as they resemble the structure or internal relationships of the original systems, aiding in the inference of complex or less understood natural phenomena.

1.7.3. Simulation

According to the Britannica Encyclopedia, simulation is a method employed in various industries, scientific fields, and education that replicates real-life events and processes in controlled test environments. Creating a simulation typically involves intricate mathematical procedures. Initially, specific rules, relationships, and operational protocols are defined, along with other variables. As these factors interact, they generate novel scenarios and potentially new rules, which continue to evolve throughout the simulation. Simulation techniques can range from simple paper-and-pencil or board-game representations of situations to advanced computer-based interactive systems.

1.7.4. Computational Modeling

As per the Britannica Encyclopedia, computer simulation refers to the utilization of computers to replicate and analyze intricate systems through the application of mathematics, physics, and computer science. A computational model encompasses multiple variables that represent the characteristics of the system under investigation. Simulation involves adjusting these variables individually or in combination and observing the resulting outcomes. By employing computer modeling, scientists can conduct a large number of simulated experiments efficiently. This extensive experimentation aids in identifying a select few laboratory experiments that are most likely to provide solutions to the problem being studied.

1.7.5. Computer Simulation

As stated in the Britannica Encyclopedia, computer simulation involves employing a computer to replicate the dynamic behavior of one system by simulating the actions of another system designed to resemble it. A simulation utilizes a computer program that incorporates a mathematical representation or model of the actual system. This model comprises equations that replicate the functional relationships present within the real system. When the program is executed, the resulting mathematical dynamics simulate the behavior of the real system, and the outcomes are presented as data.

1.7.6. Parallel Computing

It is the study, design, and implementation of algorithms in a way as to make use of multiple processors to solve a problem. The primary purpose is to solve a problem faster or a bigger problem in the same amount of time by using more processors to share the work. Wikipedia describes it as a type of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved at the same time.

1.7.7. Computational Philosophy

As explained in the Stanford Encyclopedia of Philosophy, computational philosophy refers to the utilization of mechanized computational methods to support, expand, and enhance philosophical research. Computational philosophy is not concerned with the philosophy of computers or computational techniques; instead, it involves employing computers and computational techniques as tools for philosophical inquiry. The objective is to leverage advancements in computer technology and techniques to facilitate the progress of discovery, exploration, and argumentation across various areas of philosophy.

1.7.8. Philosophy of Science

The Britannica Encyclopedia defines the philosophy of science as a field within philosophy that examines the fundamental principles, methodologies, and implications of scientific inquiry. It addresses questions regarding the nature of science, the validity of scientific theories, and the ultimate goals of scientific endeavors. This discipline intersects with metaphysics, ontology, and epistemology, particularly in exploring the connection between science and truth. The philosophy of science primarily investigates metaphysical, epistemic, and semantic aspects of scientific knowledge. Ethical concerns such as bioethics and scientific misconduct are typically categorized under ethics or science studies rather than the philosophy of science.

1.7.9. Computational Philosophy of Science

Paul Thagard in his work on Computational Philosophy of Science defined it as “the attempt to understand the structure and growth of scientific knowledge in terms of the development of computational and psychological structures. It aims to offer new accounts of the nature of theories and explanations and the processes underlying their development. Although allied with investigations in artificial intelligence and cognitive psychology, it differs in having an essential normative component”.