Wolfram Computation Meets Knowledge

Wolfram Summer School


Anand Nair

Summer School

Class of 2005


Anand Nair is an assistant professor in the College of Business at Auburn University. He received his Ph.D. degree in business administration (specializing in operations and supply chain management) from the Eli Broad Graduate School of Management at Michigan State University. Prior to his doctoral work at Michigan State University, Anand received his undergraduate (electronics engineering) and M.B.A. degrees in India and was involved in consulting assignments in the areas of enterprise resource planning, application service provision, business process re-engineering, and development of supply chain portals.

Currently, Anand is engaged in researching the areas of innovation strategy, quality management, and strategic supply chain management. His research articles have been published or are forthcoming in several leading journals in the areas of operations management, logistics, and supply chain management. He finds the complex behavior of simple programs fascinating and is exploring the underlying intuition to gain insights into business-related issues.

Anand is a member of the Academy of Management, American Society of Quality, Decision Sciences Institute, Institute for Operations Research and Management Science, and Production and Operations Management Society. He is recognized by the American Society of Quality as a Certified Quality Engineer.

Project: Mutating Turing Machines as a Metaphor for Interactive Behavior: Examining Coordination in Interorganizational Relationships

In this project behavioral issues of coordination in interorganizational relationships are examined. Business relationships are characterized by mutually influencing behaviors by firms that are related with each other in different ways. The relationship could be competitive, cooperative, or could be of a more complex (such as “coopetitive”) form. In their ongoing interaction in various forms of relationships, organizations try to influence the behavior of their counterparts. Specifically, organizations want their collaborators (such as suppliers) to think like them and share their strategic vision. Meanwhile, organizations also try to influence their competitors’ behavior to gain competitive advantage. In line with the philosophy of exploring complexity that emerges from simple rules, the complex relational dynamics are examined using the metaphor of the simplest form of two-color, two-state Turing machines. To account for the objectives of this research, interaction between two Turing machines is considered. As a part of their interaction, the machines influence their counterparts’ behavior by mutating their rule space. In particular, the machines use the mutation rule to transfer their own code at a specified location of the interacting machine’s rule space. The following four scenarios are considered:

(i) The two machines follow the same rule and have the same initial condition

(ii) The two machines follow different rules and have the same initial condition

(iii) The two machines follow the same rule and have different initial conditions

(iv) The two machines follow different rules and have different initial conditions

The results suggest that with mutation the two machines follow a rule that is different from their original rule space. While in some instances the two machines get locked into the same behavior, in other instances the behaviors of the two machines are different from each other. When the two machines follow the same rule and have the same initial condition, the resulting behavior more or less conforms to the overall population of patterns that are observed with simple Turing machines acting alone. However, in all other cases, seemingly more complex behavior was observed. The results obtained in this study are used to gain insights regarding interorganizational relationships. The study concludes by discussing theoretical and managerial implications and by presenting directions for future extensions.

Favorite Four-Color, Nearest-Neighbor, Totalistic Rule

Rule chosen: 107396

My favorite four-color totalistic cellular automaton is 107396. I find the interconnectivities among isolated structures quite interesting.