Developing Box-Pushing Behaviours Using Evolutionary Robotics

The context of this report and the IRIDIA laboratory are described in the preface. Evolutionary Robotics and the box-pushing task are presented in the introduction.The building of a test system supporting Evolutionary Robotics experiments is then detailed. This system is made of a robot simulator and a Genetic Algorithm. It is used to explore the possibility of evolving box-pushing behaviours. The bootstrapping problem is explained, and a novel approach for dealing with it is proposed, with results presented.Finally, ideas for extending this approach are presented in the conclusion.

Evaluating alternative gait strategies using evolutionary robotics

Evolutionary robitics is a branch of artificial intelligence concerned with the automatic generation of autonomous robots. Usually the form of the robit is predefined an various computational techniques are used to control the machine's behaviour. One aspect is the spontaneous generation of walking in legged robots and this can be used to investigate the mechanical requiements for efficient walking in bipeds. This paper demonstrates a bipedal simulator that spontaneously generates walking and running gaits. The model can be customized to represent a range of hominoid morphologies and used to predict performance paramets such as preferred speed and metabolic energy cost. Because it does not require any motion capture data it is particularly suitable for investigating locomotion in fossil animals. The predictoins for modern humans are highly accurate in terms of energy cost for a given speend and thus the values predicted for other bipeds are likely to be good estimates. To illustrate this the cost of transport is calculated for Australopithecus afarensis. The model allows the degree of maximum extension at the knee to be varied causing the model to adopt walking gaits varying from chimpanzee-like to human=like. The energy costs associated with these gait choices can thus be calculated and this information used to evaluate possible locomotor strategies in early hominids

Predicting the metabolic energy costs of bipedalism using evolutionary robotics

To understand the evolution of bipedalism among the homnoids in an ecological context we need to be able to estimate theenerrgetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved, this is hte only primary source of evidence available. In this paper we use evolutionary robotics techniques (genetic algoritms, pattern generators and mechanical modeling) to produce a biomimentic simulation of bipedalism based on human body dimensions. The mechnaical simulation is a seven-segment, two-dimensional model with motive force provided by tension generators representing the major muscle groups acting around the lower-limb joints. Metabolic energy costs are calculated from the muscel model, and bipedal gait is generated using a finite-state pattern generator whose parameters are produced using a genetic algorithm with locomotor economy (maximum distance for a fixed energy cost) as the fitness criterion. The model is validated by comparing the values it generates with those for modern humans. The result (maximum efficiency of 200 J m-1) is within 15% of the experimentally derived value, which is very encouraging and suggests that this is a useful analytic technique for investigating the locomotor behaviour of fossil forms. Initial work suggests that in the future this technique could be used to estimate other locomotor parameters such as top speed. In addition, the animations produced by this technique are qualitatively very convincing, which suggests that this may also be a useful technique for visualizing bipedal locomotion.

Genetic team composition and level of selection in the evolution of cooperation

In cooperative multiagent systems, agents interac to solve tasks. Global dynamics of multiagent teams result from local agent interactions, and are complex and difficult to predict. Evolutionary computation has proven a promising approach to the design of such teams. The majority of current studies use teams composed of agents with identical control rules ("geneti- cally homogeneous teams") and select behavior at the team level ("team-level selection"). Here we extend current approaches to include four combinations of genetic team composition and level of selection. We compare the performance of genetically homo- geneous teams evolved with individual-level selection, genetically homogeneous teams evolved with team-level selection, genetically heterogeneous teams evolved with individual-level selection, and genetically heterogeneous teams evolved with team-level selection. We use a simulated foraging task to show that the optimal combination depends on the amount of cooperation required by the task. Accordingly, we distinguish between three types of cooperative tasks and suggest guidelines for the optimal choice of genetic team composition and level of selection

Museum robots: multi-robot systems for public exhibition

Mobile robots provide a versatile platform for research, however they can also provide an interesting educational platform for public exhibition at museums. In general museums require exhibits that are both eye catching and exciting to the public whilst requiring a minimum of maintenance time from museum technicians. In many cases it is simply not possible to continuously change batteries and some method of supplying continous power is required. A powered flooring system is described that is capable of providing power continuously to a group of robots. Three different museum exhibit applications are described. All three robot exhibits are of a similar basic design although the exhibits are very different in appearance and behaviour. The durability and versatility of the robots also makes them extremely good candidates for long duration experiments such as those required by evolutionary robotics.

Second-order cybernetics and enactive perception

Purpose - To present an account of cognition integrating second-order cybernetics (SOC) together with enactive perception and dynamic systems theory. Design/methodology/approach - The paper presents a brief critique of classical models of cognition then outlines how integration of SOC, enactive perception and dynamic systems theory can overcome some weaknesses of the classical paradigm. Findings - Presents the critique of evolutionary robotics showing how the issues of teleology and autonomy are left unresolved by this paradigm although their solution fits within the proposed framework. Research limitations/implications - The paper highlights the importance of genuine autonomy in the development of artificial cognitive systems. It sets out a framework within which the robofic research of cognitive systems could succeed. Practical implications - There are no immediate practical implications but see research implications. Originality/value - It joins the discussion on the fundamental nature of cognitive systems and emphasise the importance of autonomy and embodiment.

Decision-Making Mechanism to Organize the Agenda of a Guide-Robot

One of the major challenges in evolutionary robotics is constituted by the need of the robot being able to make decisions on its own, in accordance with the multiple tasks programmed, optimizing its timings and power. In this paper, we present a new automatic decision making mechanism for a robot guide that allows the robot to make the best choice in order to reach its aims, performing its tasks in an optimal way. The election of which is the best alternative is based on a series of criteria and restrictions of the tasks to perform. The software developed in the project has been verified on the tour-guide robot Urbano. The most important aspect of this proposal is that the design uses learning as the means to optimize the quality in the decision making. The modeling of the quality index of the best choice to perform is made using fuzzy logic and it represents the beliefs of the robot, which continue to evolve in order to match the "external reality”. This fuzzy system is used to select the most appropriate set of tasks to perform during the day. With this tool, the tour guide-robot prepares its agenda daily, which satisfies the objectives and restrictions, and it identifies the best task to perform at each moment. This work is part of the ARABOT project of the Intelligent Control Research Group at the Universidad Politécnica de Madrid to create "awareness" in a robot guide.

Parallel Problem Solving from Nature – PPSN XIV:14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.

Evolutionary neural networks : models and applications

The scaling problems which afflict attempts to optimise neural networks (NNs) with genetic algorithms (GAs) are disclosed. A novel GA-NN hybrid is introduced, based on the bumptree, a little-used connectionist model. As well as being computationally efficient, the bumptree is shown to be more amenable to genetic coding lthan other NN models. A hierarchical genetic coding scheme is developed for the bumptree and shown to have low redundancy, as well as being complete and closed with respect to the search space. When applied to optimising bumptree architectures for classification problems the GA discovers bumptrees which significantly out-perform those constructed using a standard algorithm. The fields of artificial life, control and robotics are identified as likely application areas for the evolutionary optimisation of NNs. An artificial life case-study is presented and discussed. Experiments are reported which show that the GA-bumptree is able to learn simulated pole balancing and car parking tasks using only limited environmental feedback. A simple modification of the fitness function allows the GA-bumptree to learn mappings which are multi-modal, such as robot arm inverse kinematics. The dynamics of the 'geographic speciation' selection model used by the GA-bumptree are investigated empirically and the convergence profile is introduced as an analytical tool. The relationships between the rate of genetic convergence and the phenomena of speciation, genetic drift and punctuated equilibrium arc discussed. The importance of genetic linkage to GA design is discussed and two new recombination operators arc introduced. The first, linkage mapped crossover (LMX) is shown to be a generalisation of existing crossover operators. LMX provides a new framework for incorporating prior knowledge into GAs.Its adaptive form, ALMX, is shown to be able to infer linkage relationships automatically during genetic search.

Solar twins in M 67: evolutionary status and lithium abundance

Aims. We determine the age and mass of the three best solar twin candidates in open cluster M 67 through lithium evolutionary models. Methods. We computed a grid of evolutionary models with non-standard mixing at metallicity [Fe/H] = 0.01 with the Toulouse-Geneva evolution code for a range of stellar masses. We estimated the mass and age of 10 solar analogs belonging to the open cluster M 67. We made a detailed study of the three solar twins of the sample, YPB637, YPB1194, and YPB1787. Results. We obtained a very accurate estimation of the mass of our solar analogs in M 67 by interpolating in the grid of evolutionary models. The three solar twins allowed us to estimate the age of the open cluster, which is 3.87(-0.66)(+0.55) Gyr, which is better constrained than former estimates. Conclusions. Our results show that the 3 solar twin candidates have one solar mass within the errors and that M 67 has a solar age within the errors, validating its use as a solar proxy. M 67 is an important cluster when searching for solar twins.

Star formation in the intragroup medium and other diagnostics of the evolutionary stages of compact groups of galaxies

Context. Compact groups of galaxies are entities that have high densities of galaxies and serve as laboratories to study galaxy interactions, intergalactic star formation and galaxy evolution. Aims. The main goal of this study is to search for young objects in the intragroup medium of seven compact groups of galaxies: HCG 2, 7, 22, 23, 92, 100 and NGC 92 as well as to evaluate the stage of interaction of each group. Methods. We used Fabry-Perot velocity fields and rotation curves together with GALEX NUV and FUV images and optical R-band and HI maps. Results. (i) HCG 7 and HCG 23 are in early stages of interaction; (ii) HCG 2 and HCG 22 are mildly interacting; and (iii) HCG 92, HCG 100 and NGC 92 are in late stages of evolution. We find that all three evolved groups contain populations of young blue objects in the intragroup medium, consistent with ages < 100 Myr, of which several are younger than < 10 Myr. We also report the discovery of a tidal dwarf galaxy candidate in the tail of NGC 92. These three groups, besides containing galaxies that have peculiar velocity fields, also show extended HI tails. Conclusions. Our results indicate that the advanced stage of evolution of a group, together with the presence of intragroup HI clouds, may lead to star formation in the intragroup medium. A table containing all intergalactic HII regions and tidal dwarf galaxies confirmed to date is appended.

The young, tight, and low-mass binary TWA22AB: a new calibrator for evolutionary models? Orbit, spectral types, and temperature

Context. Tight binaries discovered in young, nearby associations are ideal targets for providing dynamical mass measurements to test the physics of evolutionary models at young ages and very low masses. Aims. We report the binarity of TWA22 for the first time. We aim at monitoring the orbit of this young and tight system to determine its total dynamical mass using an accurate distance determination. We also intend to characterize the physical properties (luminosity, effective temperature, and surface gravity) of each component based on near-infrared photometric and spectroscopic observations. Methods. We used the adaptive-optics assisted imager NACO to resolve the components, to monitor the complete orbit and to obtain the relative near-infrared photometry of TWA22 AB. The adaptive-optics assisted integral field spectrometer SINFONI was also used to obtain medium-resolution (R(lambda) = 1500-2000) spectra in JHK bands. Comparison with empirical and synthetic librairies were necessary for deriving the spectral type, the effective temperature, and the surface gravity for each component of the system. Results. Based on an accurate trigonometric distance (17.5 +/- 0.2 pc) determination, we infer a total dynamical mass of 220 +/- 21 M(Jup) for the system. From the complete set of spectra, we find an effective temperature T(eff) = 2900(-200)(+200) K for TWA22A and T(eff) = 2900(-100)(+200) for TWA22 B and surface gravities between 4.0 and 5.5 dex. From our photometry and an M6 +/- 1 spectral type for both components, we find luminosities of log(L/L(circle dot)) = -2.11 +/- 0.13 dex and log(L/L(circle dot)) = -2.30 +/- 0.16 dex for TWA22 A and B, respectively. By comparing these parameters with evolutionary models, we question the age and the multiplicity of this system. We also discuss a possible underestimation of the mass predicted by evolutionary models for young stars close to the substellar boundary.

Beryllium abundances along the evolutionary sequence of the open cluster IC 4651-A new test for hydrodynamical stellar models

Context. Previous analyses of lithium abundances in main sequence and red giant stars have revealed the action of mixing mechanisms other than convection in stellar interiors. Beryllium abundances in stars with Li abundance determinations can offer valuable complementary information on the nature of these mechanisms. Aims. Our aim is to derive Be abundances along the whole evolutionary sequence of an open cluster. We focus on the well-studied open cluster IC 4651. These Be abundances are used with previously determined Li abundances, in the same sample stars, to investigate the mixing mechanisms in a range of stellar masses and evolutionary stages. Methods. Atmospheric parameters were adopted from a previous abundance analysis by the same authors. New Be abundances have been determined from high-resolution, high signal-to-noise UVES spectra using spectrum synthesis and model atmospheres. The careful synthetic modeling of the Be lines region is used to calculate reliable abundances in rapidly rotating stars. The observed behavior of Be and Li is compared to theoretical predictions from stellar models including rotation-induced mixing, internal gravity waves, atomic diffusion, and thermohaline mixing. Results. Beryllium is detected in all the main sequence and turn-off sample stars, both slow- and fast-rotating stars, including the Li-dip stars, but is not detected in the red giants. Confirming previous results, we find that the Li dip is also a Be dip, although the depletion of Be is more modest than for Li in the corresponding effective temperature range. For post-main-sequence stars, the Be dilution starts earlier within the Hertzsprung gap than expected from classical predictions, as does the Li dilution. A clear dispersion in the Be abundances is also observed. Theoretical stellar models including the hydrodynamical transport processes mentioned above are able to reproduce all the observed features well. These results show a good theoretical understanding of the Li and Be behavior along the color-magnitude diagram of this intermediate-age cluster for stars more massive than 1.2 M(circle dot).

Inferences of evolutionary and ecological events that influenced the population structure of Plebeia remota, a stingless bee from Brazil

The present study characterised the population genetic structure of Plebeia remota through mitochondrial DNA (mtDNA) analysis and evaluated evolutionary and ecological processes that may have contributed to the species current genetic scenario. Seventy feral nests were sampled representing four geographic regions (Cunha, Curitiba, Prudentopolis, and Blumenau). Fifteen composite mtDNA haplotypes were determined and a high genetic structure was detected among all populations. The current population structure may be a result of queen philopatry and vegetation shifts caused by palaeoclimatic changes and uplift of Brazilian coastal ranges. Finally, this study strongly suggests a revision of the taxonomic status of P. remota from the Prudentopolis region.