not striving to present the most general version. The basic aim is to lead to an intuitive understanding of the definition of a basin of attraction so that the main theorem is made reasonably transparent. Moreover, the definition given below is for scalar ODEs, easily generalizable to the vector case. They can also encapsulate smooth dynamical systems in a precise sense. I have described the procedure, summarizing a variant of Chris Moore’s approach, in Velupillai (2000, Chapter 4). A perceptive

Possessing no Significance at all. This may Indicate that it is the Prices Behaving and Accumulating in the Normal Curve that Effectively Lead the Overall Correlation. P1: TIX/XYZ JWST133-c03 Printer Name: Yet to Come ALGORITHMIC INFORMATION APPROACH TO THE MARKETS 57 0.21|12 −0.47|12 −0.55|11 −0.25|11 −0.12|11 0.15|12 DJIA vs. random SP500 vs. random NASDAQ vs. random FTSE350 vs. random CAC40 vs. random DAX vs. random 6 0.19|23 −0.20|25 −0.093|20 −0.053|22 0.095|22 −0.12|24 5 −0.15|17

MARKETS 63 looking two days behind of daily closing prices one sees two consecutive losses. The algorithmic inference will say that with probability 0.129 the third day will be a loss again. In fact, as we now know, algorithmic probability will suggest that with higher probability the next day will only repeat the last values of any run of 1’s or 0’s and the empirical distribution from the market will tell us that runs of 1 s (gains) are more likely than consecutive losses (before the rounding

The role of intelligence or cognitive capacity has been recently studied in the context of experimental economics. Section 4 provides a review of the development of this literature. Nevertheless, the counterpart work in ACE is rather lacking, and so Section 5 highlights some initial progress, pointing out possible avenues for future research. Section 6 introduces the second new element, namely, modularity, and is followed by the concluding remarks which are given in Section 7. 2. Agent-based

and neuroeconomics, by incorporating the intelligence heterogeneity of human intelligence and the modularity of brain, mind and preference. This work leads to the development of neurocognitive software agents, and starts with a ‘molecular’ foundation of aggregate dynamics. More work could be done along these lines in the future. For example, personality, social preference and culture can be included. Hence, the emergent complexity in economics and psychology can be firmly connected, and,