Abstract: To evaluate the role of individual recognition in the evolution of cooperation, we formulated and analyzed a genetic algorithm model (EvCo) for playing the Iterated Prisoner's Dilemma (IPD) game. Strategies compete against each other during each generation, and successful strategies contribute more of their attributes to the next generation. Each strategy is encoded on a `chromosome' that plays the IPD, responding to the sequences of most recent responses by the interacting individuals (chromosomes). The analysis reported in this paper considered different memory capabilities (one to five previous interactions), pairing continuities (pairs of individuals remain together for about one, two, five, or 1000 consecutive interactions), and types of individual recognition (recognition capability was maximal, nil, or allowed to evolve between these limits). Analysis of the results focused on the frequency of mutual cooperation in pairwise interactions (a good indicator of overall success in the IPD) and on the extent to which previous responses by the focal individual and its partner were associated with the partner's identity (individual recognition). Results indicated that a fixed, substantial amount of individual recognition could maintain high levels of mutual cooperation even at low pairing continuities, and a significant but limited capability for individual recognition evolved under selection. Recognition generally increased mutual cooperation more when the recent responses of individuals other than the current partner were ignored. Titrating recognition memory under selection using a fitness cost suggested that memory of the partner's previous responses was more valuable than memory of the focal's previous responses. The dynamics produced to date by EvCo are a step toward understanding the evolution of social networks, for which additional benefits associated with group interactions must be incorporated.

Abstract: Thirty horses were filmed with a panning camera operating at 50 frames/s as they jumped over a 1.20 x 1.20 m fence. The markers of 9 joints on the horse and 7 joints on the rider were tracked in 2D with the TrackEye system. The centre of gravity and moment of inertia of each segment were calculated using a geometric algorithm and a cylindric model, respectively. The kinetic moment of each part of the horse was calculated after filtering, and resampling of data. This method showed the relative contribution of each body segment to the body overall rotation during the take-off, jump and landing phases. It was found that the trunk, hindlimbs and head-neck had the greatest influence. The coordination between the motion of the body segments allowed the horse to control its angular speed of rotation over the fence. This remained nearly constant during the airborne phase (120 +/- 5 degrees/s). During the airborne phase, the kinetic moment was constant because its value was equal to the moment of the external forces (722 +/- 125 kg x m2/s).

Abstract: n many animal systems agonistic interactions may be rare or not overt, particularly where such interactions are costly or of high risk as is common for large mammals. We present a technique developed specifically for resolving an optimized dominance order of individuals in systems with transitive (i.e. linear) dominance relationships, but where not all relationships are known. Our method augments the widely used I&SI method (de Vries, 1998) with an interpolation function for resolving the relative ranks of individuals with unknown relationships. Our method offers several advantages over other dominance methods by enabling the incorporation of any proportion of unknown relationships, resolving a unique solution to any dominance matrix, and calculating cardinal dominance strengths for each individual. As such, this method enables novel insight into difficult to study behavioural systems.