Information Technology Reference
In-Depth Information
15
Intelligent Biosystems and the Idea of the
Joint Synthesis of Goals and Means
Pavel N. Prudkov
Ecomon Ltd., Moscow,
Russia
1. Introduction
Immediately after the appearance of first computers more than sixty years ago, the idea of
the creation of artificial intelligence similar to that of humans has inspired activity of
thousands of outstanding individuals. Interesting results have been achieved in this
endeavor but the situation still seems unsatisfactory. With exception of very narrow
domains such as chess playing, intelligent systems cannot compete with humans or even
animals. Several factors may be the reason of this situation. In this chapter, I consider one of
the most important reasons: there are serious problems in the theory of intelligent systems
and, accordingly, in theoretical approaches to the building of artificial intelligence.
Therefore, the consideration of fundamental principles of intelligence may be an appropriate
method for constructing effective systems of AI.
Although there is no clear definition for the term 'intelligence', it is intuitively
understandable that intelligence is an attribute of goal-directed systems. A goal-directed
system has various goals, which the system attempts to achieve through interactions with
the environment based on diverse methods or means. Intelligence characterizes the efficacy
of such systems in the achievement of its goals (Russell & Norvig, 2003). Humans and
animals undoubtedly are goal-directed systems and observations of their activities reveal
two obvious classes of such systems.
One class that may underlie the activity of nonhuman animals contains goal-directed
systems in which basic goals and means are determined jointly in the moment of the
creation of a system. A system belonging to this class functions as follows: one or several
basic goals are activated along with a broad diversity of means innately associated with
those goals. In accordance with the requirements of the situation, one or several of such
means are performed and then associations between those goals and means are changed
through feedback loops using hard-wired relations between goals and the result of
performance or/and those relations generate new means, which are consequences of some
changes in ongoing means. It seems that various systems in neural nets, evolutionary
computing, reinforcement learning, etc correspond to this class of goal-directed systems
(Haykin, 1998; Bäck, 1996; Holland, 1975; Leslie et al, 1996; Sutton & Barto, 1998).
The observation of human actions and introspection allow us to define the other class in
which goals and means can be constructed arbitrarily and independently from each other. If
