Speaking: from Intention to Articulation Willem J. M. Levelt, 1989 (1993 paperback) Cambridge, MA: MIT Press ISBN: 0–262–12137–9(hb), 0–262–62089–8(pb)Rules for Reasoning Richard E. Nisbett (Ed.), 1993 Hillsdale, NJ, Lawrence Erlbaum Associates ISBN: 0–8058–1256–3(hb), 0–8085–1257–1 (pb)Readings in Philosophy and Cognitive Science Alvin I. Goldman, 1993 Cambridge, MA, MIT Press ISBN: 0–262–07153–3(hb), 0–262–57100–5(pb)Language Comprehension in Ape and Child, Monographs of the Society for Research in Child Development, Serial No. 233, Vol. 58, Nos 3–4 Sue Savage‐Rumbaugh, Jeannine Murphy, Rose A. Sevcik, Karen E. (...) Brakke, Shelly L. Williams & Duane M. Rumbaugh, with commentary by Elizabeth Bates, and a reply by the authors, 1993 Chicago: University of Chicago Press ISBN: 0–226–73542–7Language, Music and Mind Diana Raffman, 1993 Cambridge, MIT Press/Bradford Books ISBN: 0–262–18150–9Psychology of Proof Lance J. Rips, 1994 Cambridge, MA, MIT Press ISBN: 0–262–18153–3Human and Machine Thinking P. Johnson‐Laird, 1993 Hillsdale, NJ, Erlbaum ISBN: 0–8058–0921‐XIntelligent Behavior in Animals and Robots David McFarland & Thomas Bosser, 1993 Cambridge, MA and London, UK: MIT Press/ Bradford Books ISBN: 0–262–13293–1The Eye and the Mind: Reflections on Perception and the Problem of Knowledge Charles Landesman, 1993 Dordrecht: Kluwer Academic Publishers ISBN: 0–7923–2586–9The Moral Self GilG. Noam & Thomas E. Wren (Eds), in cooperation with Gertud Nunner‐Winkler & Wolfgang Edelstein, 1993 Cambridge, MA: MIT Press ISBN: 0–262–14052–1The Logic of Discovery: A Theory of the Rationality of Scientific Research Scott A. Kleiner, 1993 Dordrecht: Kluwer Academic Publishers ISBN: 0–7923–2371–8Folk Psychology and the Philosophy of Mind S.M. Christenson & D.R. Turner (Eds), 1993 Hillsdale, NJ: Lawrence Erlbaum ISBN: 0–805–80931–7. (shrink)

A considerable number of areas of bioscience, including gene and drug discovery, metabolic engineering for the biotechnological improvement of organisms, and the processes of natural and directed evolution, are best viewed in terms of a ‘landscape’ representing a large search space of possible solutions or experiments populated by a considerably smaller number of actual solutions that then emerge. This is what makes these problems ‘hard’, but as such these are to be seen as combinatorial optimisation problems that are best attacked (...) by heuristic methods known from that field. Such landscapes, which may also represent or include multiple objectives, are effectively modelled in silico, with modern active learning algorithms such as those based on Darwinian evolution providing guidance, using existing knowledge, as to what is the ‘best’ experiment to do next. An awareness, and the application, of these methods can thereby enhance the scientific discovery process considerably. This analysis fits comfortably with an emerging epistemology that sees scientific reasoning, the search for solutions, and scientific discovery as Bayesian processes. (shrink)

It is considered in some quarters that hypothesis‐driven methods are the only valuable, reliable or significant means of scientific advance. Data‐driven or ‘inductive’ advances in scientific knowledge are then seen as marginal, irrelevant, insecure or wrong‐headed, while the development of technology—which is not of itself ‘hypothesis‐led’ (beyond the recognition that such tools might be of value)—must be seen as equally irrelevant to the hypothetico‐deductive scientific agenda. We argue here that data‐ and technology‐driven programmes are not alternatives to hypothesis‐led studies in (...) scientific knowledge discovery but are complementary and iterative partners with them. Many fields are data‐rich but hypothesis‐poor. Here, computational methods of data analysis, which may be automated, provide the means of generating novel hypotheses, especially in the post‐genomic era. BioEssays 26:99–105, 2004. © 2003 Wiley Periodicals, Inc. (shrink)