Characterization of Surgical Movements As a Training Tool for Improving Efficiency.

Introduction: Surgical experience is often reflected by efficient, fluid, and well-calculated movements. For a new trainee, learning these characteristics is possible only by observation as there is no quantification system to define these factors. We analyzed surgeons' hand movements with different experience levels to characterize their movements according to experience.

Positive Feedback Loops Between Inflammatory, Bone and Cancer Cells During Metastatic Niche Construction.

Bone, which includes several cell populations and numerous cytokines and chemokines that provide cell-cell signaling, is a common destination for many cancer metastases. Bone metastasis skews this signaling to develop vicious cycles between immune, bone and cancer populations that lead to abnormal bone remodeling during cancer niche construction. Temporal models utilize positive feedback systems as an integrative tool providing insights into the rate-limiting processes that determine multiple stages of the bone metastasis.

Critical transitions in a game theoretic model of tumour metabolism.

Tumour proliferation is promoted by an intratumoral metabolic symbiosis in which lactate from stromal cells fuels energy generation in the oxygenated domain of the tumour. Furthermore, empirical data show that tumour cells adopt an intermediate metabolic state between lactate respiration and glycolysis. This study models the metabolic symbiosis in the tumour through the formalism of evolutionary game theory.

Replicator dynamics with turnover of players.

We study adaptive dynamics in games where players abandon the population at a given rate and are replaced by naive players characterized by a prior distribution over the admitted strategies. We demonstrate how such a process leads macroscopically to a variant of the replicator equation, with an additional term accounting for player turnover. We study how Nash equilibria and the dynamics of the system are modified by this additional term for prototypical examples such as the rock-paper-scissors game and different classes of two-action games played between two distinct populations.

Coevolutionary networks of reinforcement-learning agents.

This paper presents a model of network formation in repeated games where the players adapt their strategies and network ties simultaneously using a simple reinforcement-learning scheme. It is demonstrated that the coevolutionary dynamics of such systems can be described via coupled replicator equations. We provide a comprehensive analysis for three-player two-action games, which is the minimum system size with nontrivial structural dynamics.

Dynamics of Boltzmann Q learning in two-player two-action games.

We consider the dynamics of Q learning in two-player two-action games with a Boltzmann exploration mechanism. For any nonzero exploration rate the dynamics is dissipative, which guarantees that agent strategies converge to rest points that are generally different from the game's Nash equlibria (NEs). We provide a comprehensive characterization of the rest point structure for different games and examine the sensitivity of this structure with respect to the noise due to exploration.