Nelson

Over the last several decades research efforts have explored various forms of artificial life and embodied artificial life as methods for developing autonomous agents. Such approaches, although a part of the AI canon, are rarely used in research aimed at creating artificial general intelligence. This paper explores the prospects of using in silicoartificial evolution to develop machine consciousness, or strong AI. It is possible that artificial evolution and situated self-organizing agents could become viable tools for studying machine consciousness, but there are several issues that must be overcome. One problem is the use of exogenous selection methods to drive artificial evolutionary processes. A second problem relates to agent representation that is inconsistent with the environment in which the agents are situated. These issues limit the potential for open-ended evolution and fine-grained fitting of agents to environment, which are likely to be important for the eventual development of situated artificial consciousness.