Advantages of Task-Specific Multi-Objective Optimisation in Evolutionary Robotics

The application of multi-objective optimisation to evolutionary robotics is receiving increasing attention. A survey of the literature reveals the different possibilities it offers to improve the automatic design of efficient and adaptive robotic systems, and points to the successful demonstrations available for both task-specific and task-agnostic approaches (i.e., with or without reference to the specific design problem to be tackled). However, the advantages of multi-objective approaches over single-objective ones have not been clearly spelled out and experimentally demonstrated. This paper fills this gap for task-specific approaches: starting from well-known results in multi-objective optimisation, we discuss how to tackle commonly recognised problems in evolutionary robotics. In particular, we show that multi-objective optimisation (i) allows evolving a more varied set of behaviours by exploring multiple trade-offs of the objectives to optimise, (ii) supports the evolution of the desired behaviour through the introduction of objectives as proxies, (iii) avoids the premature convergence to local optima possibly introduced by multi-component fitness functions, and (iv) solves the bootstrap problem exploiting ancillary objectives to guide evolution in the early phases. We present an experimental demonstration of these benefits in three different case studies: maze navigation in a single robot domain, flocking in a swarm robotics context, and a strictly collaborative task in collective robotics.     

Simulation methods with extended stability for stiff biochemical Kinetics

Background  

With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows.     

The cell cycle modulated glycoprotein GP115 is one of the major yeast proteins containing glycosylphosphatidylinositol

The cell cycle modulated protein gp115 (115 kDa, isoelectric point about 4.8-5) of Saccharomyces cerevisiae undergoes various post-translational modifications. It is N-glycosylated during its maturation along the secretory pathway where an intermediary precursor of 100 kDa (p100), dynamically related to the mature gp115 protein, is detected at the level of endoplasmic reticulum. Moreover, we have shown by the use of metabolic labeling with [35S]methionine, [3H]palmitic acid and myo-[3H]inositol combined with high resolution two-dimensional gel electrophoresis and immunoprecipitation with a specific antiserum, that gp115 is one of the major palmitate- and inositol-containing proteins in yeast. These results, and the susceptibility of gp115 to phosphatidylinositol-specific phospholipase C treatment strongly indicate that gp115 contains the glycosylphosphatidylinositol (GPI) structure as membrane anchor domain. The two-dimensional analysis of the palmitate- and inositol-labeled proteins has also allowed the characterization of other polypeptides which possibly contain a GPI structure.