David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Both the irreducible complexity of biological phenomena and the aim of a universalized biology (life-as-it-could-be) have lead to a deep methodological shift in the study of life; represented by the appearance of ALife, with its claim that computational modelling is the main tool for studying the general principles of biological phenomenology. However this methodological shift implies important questions concerning the aesthetic, engineering and specially the epistemological status of computational models in scientific research: halfway between the well established categories of theory and experiment. ALife models become powerful epistemic artefacts allowing the simulation of emergent phenomena, the interaction between different levels of organization and the integration of different causal factors in the very same manipulable object. The use of computational models in ALife can be classified in four main categories depending on their position between theoretical and empirical practices: generic, conceptual, functional and mechanistic. For each of these categories we analyse their epistemic value and select paradigmatic examples that illustrate how ALife models can be fruitfully inserted in the study of life.
|Keywords||No keywords specified (fix it)|
No categories specified
(categorize this paper)
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library||
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Tarja Knuuttila (2011). Modelling and Representing: An Artefactual Approach to Model-Based Representation. Studies in History and Philosophy of Science 42 (2):262-271.
Brian L. Keeley (1998). Artificial Life for Philosophers. Philosophical Psychology 11 (2):251 – 260.
Sven Diekmann & Martin Peterson (2013). The Role of Non-Epistemic Values in Engineering Models. Science and Engineering Ethics 19 (1):207-218.
John Symons (2008). Computational Models of Emergent Properties. Minds and Machines 18 (4):475-491.
Liz Stillwaggon Swan (2009). Synthesizing Insight: Artificial Life as Thought Experimentation in Biology. Biology and Philosophy 24 (5):687-701.
John P. Sullins (2005). Ethics and Artificial Life: From Modeling to Moral Agents. [REVIEW] Ethics and Information Technology 7 (3):139-148.
Rodney Brooks (2001). The Relationship Between Matter and Life. Nature 409 (6818):409-411.
Added to index2009-11-21
Total downloads16 ( #116,578 of 1,410,275 )
Recent downloads (6 months)1 ( #177,872 of 1,410,275 )
How can I increase my downloads?