We investigate a version of the classic Colonel Blotto game in which individual battles may have different values. Two players allocate a fixed budget across battlefields and each battlefield is won by the player who allocates the most to that battlefield. The winner of the game is the player who wins the battlefields with highest total value. We focus on the case where there is one large and several small battlefields, such that a player wins if he wins the large and any one small battlefield, or all the small battlefields. We compute the mixed strategy equilibrium for these games and compare this with choices from a laboratory experiment. The equilibrium predicts that the large battlefield receives more than a proportional share of the resources of the players, and that most of the time resources should be spread over more battlefields than are needed to win the game. We find support for the main qualitative features of the equilibrium. In particular, strategies that spread resources widely are played frequently, and the large battlefield receives more than a proportional share in the treatment where the asymmetry between battlefields is stronger.This network project brings together economists, psychologists, computer and complexity scientists from three leading centres for behavioural social science at Nottingham, Warwick and UEA. This group will lead a research programme with two broad objectives: to develop and test cross-disciplinary models of human behaviour and behaviour change; to draw out their implications for the formulation and evaluation of public policy. Foundational research will focus on three inter-related themes: understanding individual behaviour and behaviour change; understanding social and interactive behaviour; rethinking the foundations of policy analysis. The project will explore implications of the basic science for policy via a series of applied projects connecting naturally with the three themes. These will include: the determinants of consumer credit behaviour; the formation of social values; strategies for evaluation of policies affecting health and safety. The research will integrate theoretical perspectives from multiple disciplines and utilise a wide range of complementary methodologies including: theoretical modeling of individuals, groups and complex systems; conceptual analysis; lab and field experiments; analysis of large data sets. The Network will promote high quality cross-disciplinary research and serve as a policy forum for understanding behaviour and behaviour change.

Experimental data. The experiment was conducted with 148 subjects recruited from a university-wide pool of undergraduate students using ORSEE (Greiner, 2004). The experiment consisted of nine computerized sessions, with no subject participating in more than one session. The experiment was programmed in z-tree (Fischbacher, 2007).