David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
It is often thought that there is one key design principle or at best a small set of design principles, underlying the success of biological organisms. Candidates include neural nets, ‘swarm intelligence’, evolutionary computation, dynamical systems, particular types of architecture or use of a powerful uniform learning mechanism, e.g. reinforcement learning. All of those support types of self-organising, self-modifying behaviours. But we are nowhere near understanding the full variety of powerful information-processing principles ‘discovered’ by evolution. By attending closely to the diver- sity of biological phenomena we may gain key insights into (a) how evolution happens, (b) what sorts of mechanisms, forms of representation, types of learning and development and types of architectures have evolved, (c) how to explain ill-understood aspects of human and animal intelligence, and (d) new useful mechanisms for artiﬁcial systems.
|Keywords||No keywords specified (fix it)|
|Categories||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
Vinod Goel (1991). Notationality and the Information Processing Mind. Minds and Machines 1 (2):129-166.
George Rzevski & Kumkum Prasad (1998). The Synergy of Learning Organisations and Flexible Information Technology. AI and Society 12 (1-2):87-96.
David Chalmers (1992). The Evolution of Learning: An Experiment in Genetic Connectionism. In Connectionist Models: Proceedings of the 1990 Summer School Workshop. Morgan Kaufmann.
Leslie P. Tolbert, Lynne A. Oland, Thomas C. Christensen & Anita R. Goriely (2003). Neuronal and Glial Morphology in Olfactory Systems: Significance for Information-Processing and Underlying Developmental Mechanisms. [REVIEW] Brain and Mind 4 (1):27-49.
P. Tolbert Leslie, A. Oland Lynne, C. Christensen Thomas & R. Goriely Anita (2003). Neuronal and Glial Morphology in Olfactory Systems: Significance for Information-Processing and Underlying Developmental Mechanisms. Brain and Mind 4 (1).
Aaron Sloman, The ``Semantics'' of Evolution: Trajectories and Trade-Offs in Design Space and Niche Space.
G. Tesauro, D. Touretzky & T. Leen (eds.) (1995). Advances in Neural Information Processing Systems 7. MIT Press.
Gordana Dodig-Crnkovic (2011). Significance of Models of Computation, From Turing Model to Natural Computation. Minds and Machines 21 (2):301-322.
Ian Wright, Aaron Sloman & Luc Beaudoin (1996). Towards a Design-Based Analysis of Emotional Episodes. Philosophy, Psychiatry, and Psychology 3 (2):101-126.
Me Burke, Philosophical and Theoretical Perspectives of Organisational Structures as Information Processing Systems.
François Chapeau-Blondeau (1995). Information Processing in Neural Networks by Means of Controlled Dynamic Regimes. Acta Biotheoretica 43 (1-2).
Nir Fresco (2013). Information Processing as an Account of Concrete Digital Computation. Philosophy and Technology 26 (1):31-60.
Gordana Dodig Crnkovic & Mark Burgin (eds.) (forthcoming). INFORMATION AND COMPUTATION. World Scientific.
Gualtiero Piccinini & Andrea Scarantino (2011). Information Processing, Computation, and Cognition. Journal of Biological Physics 37 (1):1-38.
Added to index2010-12-22
Total downloads3 ( #297,395 of 1,102,744 )
Recent downloads (6 months)1 ( #296,833 of 1,102,744 )
How can I increase my downloads?