The Application of Game Theory to Thermoeconomics
Last year, we proposed a relationship between physical entropy, S and abstract, yet quantifiable information, I, where entropy has units of J K−1 and information has units of bits (Layton, 2010). Therein, we proposed the relation ΔS = αI, where ΔS = Smax – Smin, with Smax representing the maximum entropy generation rate of a given system, Smin representing the reduction of internal entropy of the system for a given cycle or process, and I representing the information required to perform the cycle or process. The newly introduced coefficient, α with units of J K−1 b−1 was introduced to relate a system’s ability to partition entropy via its inherent information processing capabilities (Turing, 1948). Herein we further develop this equation in an engineering context and explore the social implications of energy conservation through a lens of game theory, concluding that “sustainable” practices, rather than extending the horizon when we will consume the last of the exhaustible fuels, actually have no effect on the point in time at which fossil fuels become exhausted.