Donald Mathis, Michael C. Mozer
We propose a computational framework for understanding and modeling human consciousness. This framework integrates many existing theoretical perspectives, yet is sufficiently concrete to allow simulation experiments. We do not attempt to explain qualia (sub(cid:173) jective experience), but instead ask what differences exist within the cognitive information processing system when a person is con(cid:173) scious of mentally-represented information versus when that infor(cid:173) mation is unconscious. The central idea we explore is that the con(cid:173) tents of consciousness correspond to temporally persistent states in a network of computational modules. Three simulations are de(cid:173) scribed illustrating that the behavior of persistent states in the models corresponds roughly to the behavior of conscious states people experience when performing similar tasks. Our simulations show that periodic settling to persistent (i.e., conscious) states im(cid:173) proves performance by cleaning up inaccuracies and noise, forcing decisions, and helping keep the system on track toward a solution.