Aggression is wide-spread in nature and seems to serve, among others, an important role in the interspecies competition for resources. In this paper, we argue that displaying aggression as a means to signal action tendencies (in particular, the probability to continue an encounter) is beneficial for social groups and show that discriminating between “own ” and “other” is more beneficial than treating “other ” the same as “own”. In particular, we demonstrate that aggression plays a crucial role in strategies applied to “other”. To test the theoretical discussion, we define a seven basic agent types which give rise to 42 different discriminating agents, i.e., agents with different strategies for “own ” and “other”. In extensive simulation studies we show that discriminating agents, which assume an aggressive attitude towards others, while playing a strategy that distributes resources fairly among “own”, are ultimately the most successful ones. We discuss the implications of these results for natural and artificial agents and conclude with a brief outlook on further studies. 1.

Conflicts over resources can be resolved in many ways, from fighting to sharing.

Question: How can the evolution of turn-taking be explained in species without language? Features of model: Using a genetic algorithm incorporating mutation and crossover, we studied noisy decision making in three repeated two-player games in which we predicted on theoretical grounds that cooperative turn-taking would evolve and three games in which we expected synchronized cooperation to evolve. Ranges of key variables: We set population size to 20, number of rounds to be played by each pair in each generation to 200, and number of evolutionary generations to 2000, and we repeated each simulation 10 times to check the stability of the results. Results: Cooperative turn-taking and (unexpectedly) a form of double turn-taking evolved in the alternation games, and joint cooperation evolved in the synchronization games. We propose a mechanism to explain how cooperative turn-taking can evolve mechanically, even without communication or insight, as it did in our simulations.

We investigate the interactions between conflict resolution and survival in multi-agent environments, where agents compete for resources. We define strategies for the “conflict game ” and the “survival game, ” analyze their properties, and compare their performance in agent-based simulations. The results demonstrate that inferior strategies in conflict games can be turned into superior strategies in the survival game if combined with the right parameters for foraging.

Two individuals have a regular task to complete that requires the effort of only one. Some days it is less costly for one of the individuals to complete the task, and some days it is less costly for the other individual. Each knows only their own cost. Taking turns is fair, but rigid turn-taking cannot account for changing costs. The person obligated might not be best suited for the job. A natural solution is to allow some flexibility- swapping turns when efficient. These arrangements are so familiar, we rarely think of them as economic mechanisms, but doing so provides interesting insights into their properties and performance. In this paper, I model flexible turn-taking as a simple dynamic mechanism (recurring rotation), derive theoretical properties of the mechanism and present results of an experiment designed to test these properties. Although the efficiency achieved by subjects is close to the expected efficiency, behavioral anomalies that cannot be explained by social preferences or strategic concerns suggest that subjects may be used to a different form of flexible turn-taking. An alternative form of flexible turn-taking (obligation takeover) retains familiar structure, is consistent with patterns of subject behavior, and can achieve approximately the same efficiency as an optimal mechanism using money transfers under uniformly distributed costs.

of Technology for providing me with a productive and enjoyable research environment. I would like to express my deepest gratitude to my adviser, Thomas Palfrey, for his excellent guidance, care, patience and belief. This thesis would not have been possible without his unconditional and undying support. I am also grateful to Peter Bossaerts, Federico Echenique, John Ledyard, Charles Plott, Howard Rosenthal and Matthew Shum for their care and encouragement. I have learnt a lot from their knowledge and experience. A special thanks to Laurel Auchampaugh for always being there, Chris Crabbe for developing the experimental software, both Walter Yuan and Estela Hopenhayn at UCLA for helping me with the experiments, Victoria Mason for making sure that I have enough petty cash to run my experiments on time and Eric Bax for the enjoyable time while I was