Excerpt on Cognitive Synergy and AGI Architecture (CogPrime)

144 8 Cognitive Synergy regarding the measurement of the simplicity of goals and environments; but the points made here do not rely on that argument. What they do rely on is the assumption that, in the intelligence in question, the different components of memory are significantly but not wholly distinct. That is, there are significant “family resemblances” between the memories of a single type, yet there are also thoroughgoing connections between memories of different types. The cognitive synergy principle, if correct, applies to any AI system demonstrating intelli- gence in the context of embodied, social communication. However, one may also take the theory as an explicit guide for constructing AGI systems; and of course, the bulk of this book describes one AGI architecture, CogPrime, designed in such a way. It is possible to cast these notions in mathematical form, and we make some efforts in this direction in Appendix ??, using the languages of category theory and information geometry. However, this formalization has not yet led to any rigorous proof of the generality of cognitive synergy nor any other exciting theorems; with luck this will come as the mathematics is further developed. In this chapter the presentation is kept on the heuristic level, which is all that is critically needed for motivating the CogPrime design. 8.2 Cognitive Synergy The essential idea of cognitive synergy, in the context of multi-cmemory systems, may be ex- pressed in terms of the following points: 1. Intelligence, relative to a certain set of environments, may be understood as the capability to achieve complex goals in these environments. 2. With respect to certain classes of goals and environments (see Chapter 9 for a hypothe- sis in this regard), an intelligent system requires a “multi-memory” architecture, meaning the possession of a number of specialized yet interconnected knowledge types, including: declarative, procedural, attentional, sensory, episodic and intentional (goal-related). These knowledge types may be viewed as different sorts of patterns that a system recognizes in itself and its environment. Knowledge of these various different types must be interlinked, and in some cases may represent differing views of the same content (see Figure ?7) 3. Such a system must possess knowledge creation (i.e. pattern recognition / formation) mech- anisms corresponding to each of these memory types. These mechanisms are also called “cognitive processes.” 4, Each of these cognitive processes, to be effective, must have the capability to recognize when it lacks the information to perform effectively on its own; and in this case, to dynamically and interactively draw information from knowledge creation mechanisms dealing with other types of knowledge 5. This cross-mechanism interaction must have the result of enabling the knowledge creation mechanisms to perform much more effectively in combination than they would if operated non-interactively. This is “cognitive synergy.” While these points are implicit in the theory of mind given in [GoeN6al], they are not articulated in this specific form there. Interactions as mentioned in Points 4 and 5 in the above list are the real conceptual meat of the cognitive synergy idea. One way to express the key idea here is that most AI algorithms suffer from combinatorial explosions: the number of possible elements to be combined in a HOUSE_OVERSIGHT_013060