Consciousness without inner models: A sensorimotor account of what is going on in our heads

Organising Committee
  1. Mark Addis
  2. Fernand Gobet
  3. Peter Lane
  4. Peter Sozou
Date: Tuesday 1st April Website: Description:
For full details, including format for submissions, see All questions, queries and paper submissions to: Science is fundamentally about explaining phenomena in the world. It involves an interplay between theories (hypotheses describing mechanisms or rules governing processes) and data (observations and measurements). There have been important advances in computational power, software, logic and statistical analysis techniques, together with, in many instances, an increase in the availability of data. These developments are enabling computers and computational devices to play an increasing role in the process of science. Specific developments have included: the use of evolutionary computation techniques to develop scientific theories and models, automation of the collection and analysis of data in the lab, new techniques in interpreting and analysing data, and developments in the availability of data with application to advancing science. This symposium welcomes papers on any aspect of these developments. A keynote talk will be given by Professor Ross King, Manchester Institute of Biotechnology. (See, for example, "The automation of science", Science, 324(5923), 85-89, 2009.) TOPICS OF INTEREST Submissions are invited from a range of disciplines, facilitating cross-fertilisation of ideas and techniques. Examples of suitable topics are:
  • Computational methods for automating the generation and refinement of scientific theories and models
  • Computational simulation of, and assistance with, aspects of scientific discovery such as induction, insight, creativity and theory formation
  • Computational methods for automating the collection and analysis of data in the laboratory
  • Computational methods for obtaining data in the field and in cyberspace
  • Computational methods for extracting information from data, including pattern recognition, with application to scientific discovery
  • Methods for generalising the representation of data to facilitate the development of scientific models
  • Computational methods in inverse problems in science
  • Implications of computational scientific discovery for questions concerning explanation and inference in science
We invite contributions from the physical sciences, biosciences, behavioural sciences, medical sciences, social sciences, mathematics, and philosophy of science. We welcome papers covering all relevant techniques and approaches.