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ABSTRACT: To design, to study, and to control mixed animals-robots societies is a challenging field of scientific exploration that can bring new frameworks to study individual and collective behaviors in animal and mixed robot-animal societies. In the Chicken Robot project we aim at developing a mobile robot, able to collaborate with a group of chicks and to control certain group behaviors. The first research step is to build formal models of relevant animal behaviors by performing ethological experiments. Hence, one of the principal tasks is to design a setup equipped with appropriate monitoring tools. In this paper, we present a toolset for running chick-robot experiments and analyzing results. It includes an autonomous PoulBot robot and an experimental setup, able to autonomously record experimental video and audio data, to detect displacements of chicks and robots, to detect their calling activity and to provide robots with these data. We also present a visual data analysis system to extract behavioral features of individual chicks using the variational Bayesian Gaussian mixture model classification with a particle filters based prediction of future positions of chicks. We show how these tools are currently used to carry out chick-robot experiments, to collect behavioral data and to extract animal behavioral features that allow us to build behavioral models bound to be implemented in the robot.
Intelligent Robots and Systems (IROS), 2010 IEEE/RSJ International Conference on; 11/2010
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J Halloy,
G Sempo,
G Caprari,
C Rivault,
M Asadpour,
F Tâche,
I Saïd,
V Durier,
S Canonge,
J M Amé,
C Detrain,
N Correll,
A Martinoli,
F Mondada,
R Siegwart,
J L Deneubourg
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ABSTRACT: Collective behavior based on self-organization has been shown in group-living animals from insects to vertebrates. These findings have stimulated engineers to investigate approaches for the coordination of autonomous multirobot systems based on self-organization. In this experimental study, we show collective decision-making by mixed groups of cockroaches and socially integrated autonomous robots, leading to shared shelter selection. Individuals, natural or artificial, are perceived as equivalent, and the collective decision emerges from nonlinear feedbacks based on local interactions. Even when in the minority, robots can modulate the collective decision-making process and produce a global pattern not observed in their absence. These results demonstrate the possibility of using intelligent autonomous devices to study and control self-organized behavioral patterns in group-living animals.
Science 12/2007; 318(5853):1155-8. · 31.20 Impact Factor
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ABSTRACT: The spatial distribution of individuals is an important subject in many fields because it conditions the levels of interactions
among individuals, and more generally the structuring as well as the organization of populations. Increase in density of individuals
in a given area can be induced by environmental stimuli and/or by interactions among individuals (1–3). Thus, various definitions
of aggregation have been given, ecologists privilege the importance of environmental stimuli, while others privilege existing
relationships between group members.
Aggregation is one of the most widespread social phenomena and occurs at all biological levels, from bacteria to mammals including
humans (4, 5). If sometimes, aggregation is associated to non-adaptive, often it is the ground on which more complex social
structures are built such as synchronization or division of labour (6). However, knowledge of the mechanisms implied in the
formation of aggregates remains fragmentary. The study of the proximal causes, i.e. mechanisms involved in group formation,
can benefit from concepts of self-organization (5, 7). These groups find their origin and their cohesion in the inter-attraction
among individuals: group members are then the source of attraction. However, in most of the situations, patterns of aggregation,
resulting from individual responses to conspecifics are modulated by environmental heterogeneity (5).
Previous studies on cockroaches have already described their aggregative distribution in a natural environment where different
age-classes share the resources that are present in their home range. They exhibit a strong tendency to gather during their
resting period in safe shelters. Therefore, shelters are important, but also limited environmental resources for these insects.
The basic mechanisms underlying group formation is the modulation of the individual resting time as a function of the number
of conspecifics on a site. In insects cuticular hydrocarbons act as a recognition signal allowing attraction between individuals
(8). Cockroaches prefer their own strain odour to another strain (9). Nevertheless, when groups in tests came from two different
strains, they aggregated on one site only and did not show any difference from group coming from one strain.
We used this insect as an example to show that a self-organized process leads to a diversity of optimal patterns without modification
of the individual behaviours and any general knowledge of the available resources. These experimental and theoretical results
point to a generic self-organized pattern-formation process independent of the level of animal sociability that should be
found in other group-living organisms that present inter-attraction.
12/2006: pages 455-463;
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ABSTRACT: Tracking of miniature robotic platforms involves major challenges in image recognition and data association. We present our 3-year effort into developing the platform-independent, easy-to-use, and robust tracking software SwisTrack, which is tailored to research in swarm robotics and behavioral biology. We demonstrate the software and algorithms abilities using two case studies, tracking of a swarm of cockroaches, and a swarm-robotic inspection task, while outlining hard problems in tracking and data-association of marker-less objects. Tracking accuracy of a moving robot with respect to camera noise and the calibration model are calculated experimentally. Its open, platform-independent architecture, and easy-to-use interfaces (Matlabtrade, Javatrade, and C++), allowing for (distributed) post-processing of trajectory data online, make the software highly adaptive to particular research projects without changes to the source code. SwisTrack is publicly available on Sourceforge.net under the OSI Adaptive License and contributions from the robotics and biology community are encouraged
Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on; 11/2006
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ABSTRACT: Amplification is the main component of many collective phenomena in social and gregarious insects. In a society, individuals face a mixed palette of odours coming from different groups (lines, strains) and individuals present discrimination capabilities. However, often at the collective level, different groups may cooperate and act together. To understand this apparent contradiction, we use a model of food recruitment where each group of foragers have its own blend of pheromone trail that is partly recognized by the others groups. The model shows that a low level of recognition between signals is sufficient to produce a collaborative pattern between groups and that beyond a critical value of recognition, only the aggregation of all the groups around the same food source is observed. The comparison between this model and one describing the site selection by gregarious insects (e.g. cockroach) suggests that such collective response is a generic property of social phenomena governed by amplification processes.
Journal of Theoretical Biology 05/2006; 239(3):313-23. · 2.21 Impact Factor
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ABSTRACT: In this paper, we show how self-* mechanisms give rise to complex but predictable and therefore steerable global system behavior in a cooperative computing environment. We simulate the operation of and interactions between a set of networked autonomic devices. These are used as access points to a number of services, have the ability to accept or delegate execution of the associated tasks, and can adjust their internal state in response to the demand. We study the emergence of cooperation, and find that it spontaneously occurs when specific conditions are met that allow individual devices to focus on performing a single task, sacrificing their ability to efficiently perform others
Autonomic Computing, 2005. ICAC 2005. Proceedings. Second International Conference on; 07/2005
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ABSTRACT: This paper presents the European project LEURRE which deals with the cooperation between robots and animals in a social context. Its main objective is to demonstrate the possible control of such mixed societies. The control of interactions between artificial systems and living organisms is a key challenge in many scientific fields like medicine, agriculture, and ethology. All biological levels are concerned: the cellular level regarding, for example, interfaces between artificial systems and cells like neurons; the organism level regarding intelligent prosthesis; and the human level as it relates to cooperation between humans and robots. For research dealing with animal societies, it is convenient to use animals that allow detailed analysis and modeling. For this reason, gregarious insects are a good choice. The artificial agent in the mixed society is an autonomous mobile robot. The recent results achieved in this field allows the design of a miniature robot with sufficient performance to interact with insects. It is called InsBot for "insect-like robot". To achieve the goals, American cockroaches and miniature robots were used to form the experimental mixed society.
IEEE Robotics & amp amp Automation Magazine 07/2005; · 1.99 Impact Factor
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ABSTRACT: Circadian rhythms, characterized by a period of about 24h, are generated in nearly all living organisms by the negative autoregulation of clock gene expression. Deterministic models based on this genetic regulation account for circadian oscillations in constant environmental conditions (e.g., in constant darkness) and for entrainment of these rhythms by light-dark cycles. When the number of clock mRNA and protein molecules is low, it is necessary to resort to stochastic simulations to assess the influence of molecular noise on circadian oscillations. Indeed, it is possible that the autoregulatory mechanism of gene expression might not produce stable rhythms due to fluctuations if the number of molecules involved in the clock mechanism remains too low. We have compared the deterministic and stochastic approaches for a model based on the negative autoregulation of a clock gene. We show by means of stochastic simulations that robust circadian oscillations can already occur when the maximum number of mRNA and protein molecules is of the order of a few tens or hundreds, respectively. Furthermore, the results indicate that the cooperativity characterizing the repression of the transcription process strenghtens the robustness of circadian rhythms and that entrainment by light-dark cycles stabilizes the phase of the oscillations.
Pathologie Biologie 07/2003; 51(4):227-30. · 1.53 Impact Factor
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ABSTRACT: Circadian rhythms which occur with a period close to 24 h in nearly all living organisms originate from the negative autoregulation of gene expression.Deterministic models based on genetic regulatory processes account for theoccurrence of circadian rhythms in constant environmental conditions (e.g.constant darkness), for entrainment of these rhythms by light-dark cycles, and for their phase-shifting by light pulses. At low numbers of protein and mRNA molecules, it becomes necessary to resort to stochastic simulations to assess the influence of molecular noise on circadian oscillations. We address the effect of molecular noise by considering two stochastic versions of a core model for circadian rhythms. The deterministic version of this core modelwas previously proposed for circadian oscillations of the PER protein in Drosophila and of the FRQ protein in Neurospora. In the first, non-developed version of the stochastic model, we introduce molecular noise without decomposing the deterministic mechanism into detailed reaction steps while in the second, developed version we carry out such a detailed decomposition. Numerical simulations of the two stochastic versions of the model are performed by means of the Gillespie method. We compare the predictions of the deterministic approach with those of the two stochastic models, with respect both to sustained oscillations of the limit cycle type and to the influence of the proximity of a bifurcation point beyond which the system evolves to a stable steady state. The results indicate that robust circadian oscillations can occur even when the numbers of mRNA and nuclear protein involved in the oscillatory mechanism are reduced to a few tens orhundreds, respectively. The non-developed and developed versions of the stochastic model yield largely similar results and provide good agreement with the predictions of the deterministic model for circadian rhythms.
Journal of Biological Physics 12/2002; 28(4):637-53. · 1.86 Impact Factor
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ABSTRACT: We report a study of the influence of molecular fluctuations on a limit-cycle model of circadian rhythms based on the regulatory network of a gene involved in a biochemical clock. The molecular fluctuations may become important because of the low number of molecules involved in such genetic regulatory networks at the subcellular level. The molecular fluctuations are described by a birth-and-death stochastic process ruled by the chemical master equation of Nicolis and co-workers and simulated by Gillespie’s algorithm. The robustness of the oscillations is characterized, in particular, by the probability distribution of the first-return times and the autocorrelation functions of the noisy oscillations. The half-life of the autocorrelation functions is studied as a function of the size of the system which controls the magnitude of the molecular fluctuations and of the degree of cooperativity of some reaction steps of the biochemical clock. The role of the attractivity of the limit cycle is also discussed. © 2002 American Institute of Physics.
The Journal of Chemical Physics 06/2002; 116(24):10997-11010. · 3.33 Impact Factor
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ABSTRACT: Human scalp hair consists of a set of about 10(5)follicles which progress independently through developmental cycles. Each hair follicle successively goes through the anagen (A), catagen (C), telogen (T) and latency (L) phases that correspond, respectively, to growth, arrest and hair shedding before a new anagen phase is initiated. Long-term experimental observations in a group of ten male, alopecic and non-alopecic volunteers allowed determination of the characteristics of hair follicle cycles. On the basis of these observations, we previously proposed a follicular automaton model to simulate the dynamics of human hair cycles and the development of different patterns of alopecia [Halloy et al. (2000) Proc. Natl Acad. Sci. U.S.A.97, 8328-8333]. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states A, T, L and the subsequent return to A. These transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a standard deviation. The follicular automaton model was shown to account both for the dynamical transitions observed in a single follicle, and for the behaviour of an ensemble of independently cycling follicles. Here, we extend these results and investigate additional properties of the model. We present a deterministic version of the follicular automaton. We show that numerical simulations of the stochastic version of the automaton yield steady-state level of follicles in the different phases which approach the levels predicted by the deterministic equations as the number of follicles progressively increases. Only the stochastic version can successfully reproduce the fluctuations of the fractions of follicles in each of the three phases, observed in small follicle populations. When the standard deviation is reduced or when the follicles become otherwise synchronized, e.g. by a periodic external signal inducing the transition of anagen follicles into telogen phase, large-amplitude oscillations occur in the fractions of follicles in the three phases. These oscillations are not observed in humans but are reminiscent of the phenomenon of moulting observed in a number of mammalian species.
Journal of Theoretical Biology 03/2002; 214(3):469-79. · 2.21 Impact Factor
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ABSTRACT: The hair follicle cycle successively goes through the anagen, catagen, telogen, and latency phases, which correspond, respectively, to hair growth, arrest, shedding, and absence before a new anagen phase is initiated. Experimental observations collected over a period of 14 years in a group of 10 male volunteers, alopecic and nonalopecic, allowed us to determine the characteristics of scalp hair follicle cycles. On the basis of these observations, we propose a follicular automaton model to simulate the dynamics of human hair cycles. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states anagen, telogen, and latency, and the subsequent return to anagen. The transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a variance. The follicular automaton model accounts both for the dynamical transitions observed in a single follicle and for the behavior of an ensemble of independently cycling follicles. Thus, the model successfully reproduces the evolution of the fractions of follicle populations in each of the three phases, which fluctuate around steady-state or slowly drifting values. We apply the follicular automaton model to the study of spatial patterns of follicular growth that result from a spatially heterogeneous distribution of parameters such as the mean duration of anagen phase. When considering that follicles die or miniaturize after going through a critical number of successive cycles, the model can reproduce the evolution to hair patterns similar to well known types of diffuse or androgenetic alopecia.
Proceedings of the National Academy of Sciences 08/2000; 97(15):8328-33. · 9.68 Impact Factor
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ABSTRACT: Examples of pulsatile signalling abound in intercellular communication, suggesting that this phenomenon represents a major function of biological rhythms. Pulsatile signals can be encoded in terms of their frequency and prove more efficient than monotonous ones whenever constant stimulation induces desensitization of target cells. We address the main examples of frequency encoding of pulsatility, besides those of neuronal nature. Considered in turn are cAMP oscillations in the slime mould Dictyostelium discoideum, the pulsatile secretion of hormones such as gonadotropin-releasing hormone or growth hormone, intracellular Ca2+ oscillations, and circadian rhythms. Models based on receptor desensitization show the possibility of optimizing cellular responses to cAMP signals in Dictyostelium or to pulsatile hormonal stimulation. The models indicate how the optimal duration of the pulsatile signal and the optimal interval between successive pulses vary as a function of the rates or receptor desensitization and resensitization and of the maximum ligand level during stimulation. The frequency encoding of intracellular Ca2+ oscillations appears to rely on another molecular mechanism. Models based on protein phosphorylation by a Ca(2+)-calmodulin activated kinase show that the mean level of phosphorylated protein increases with the frequency of calcium spikes--which itself rises with the degree of stimulation--and that distinct levels of different phosphorylated proteins can be reached for a Ca2+ signal of given frequency.
Novartis Foundation symposium 02/2000; 227:19-36; discussion 36-45.
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ABSTRACT: We analyze the spatial propagation of wave-fronts in a biochemical model for a product-activated enzyme reaction with non-linear recycling of product into substrate. This model was previously studied as a prototype for the coexistence of two distinct types of periodic oscillations (birhythmicity). The system is initially in a stable steady state characterized by the property of multi-threshold excitability, by which it is capable of amplifying in a pulsatory manner perturbations exceeding two distinct thresholds. In such conditions, when the effect of diffusion is taken into account, two distinct wave-fronts are shown to propagate in space, with distinct amplitudes and velocities, for the same set of parameter values, depending on the magnitude of the initial perturbation. Such a multiplicity of propagating wave-fronts represents a new type of coexistence of multiple modes of dynamic behavior, besides the coexistence involving, under spatially homogeneous conditions, multiple steady states, multiple periodic regimes, or a combination of steady and periodic regimes.
Biophysical Chemistry 10/1998; 74(3):197-207. · 2.20 Impact Factor
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ABSTRACT: We examine the theoretical aspects of temporal and spatiotemporal organization in the cAMP signaling system of Dictyostelium discoideum amoebae which aggregate in a wavelike manner after starvation, in response to pulses of cAMP emitted with a periodicity of several minutes by cells behaving as aggregation centers. We first extend the model based on receptor desensitization, previously proposed by Martiel and Goldbeter, by incorporating the role of G proteins in signal transduction. The extended model accounts for observations on the response of the signaling system to successive step increases in extracellular cAMP. In the presence of the positive feedback loop in cAMP synthesis, this model generates sustained oscillations in cAMP and in the fraction of active cAMP receptor, similar to those obtained in the simpler model where the role of the G proteins is not taken into account explicitly. We use the latter model to address the formation of concentric and spiral waves of cAMP in the course of D. discoideum aggregation. Previous analyses of the model showed that a progressive increase in the activity of adenylate cyclase and phosphodiesterase can account for the transitions no relay-relay-oscillations-relay observed in the experiments. We show that the degree of cellular synchronization on such a developmental path in parameter space markedly affects the nature of the spatial patterns generated by the model. These patterns range from concentric waves to a small number of large spirals, and finally to a large number of smaller spirals, as the degree of developmental desynchronization between cells increases.
Biophysical Chemistry 06/1998; 72(1-2):9-19. · 2.20 Impact Factor
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ABSTRACT: Whereas it is relatively easy to account for the formation of concentric (target) waves of cAMP in the course of Dictyostelium discoideum aggregation after starvation, the origin of spiral waves remains obscure. We investigate a physiologically plausible mechanism for the spontaneous formation of spiral waves of cAMP in D. discoideum. The scenario relies on the developmental path associated with the continuous changes in the activity of enzymes such as adenylate cyclase and phosphodiesterase observed during the hours that follow starvation. These changes bring the cells successively from a nonexcitable state to an excitable state in which they relay suprathreshold cAMP pulses, and then to autonomous oscillations of cAMP, before the system returns to an excitable state. By analyzing a model for cAMP signaling based on receptor desensitization, we show that the desynchronization of cells on this developmental path triggers the formation of fully developed spirals of cAMP. Developmental paths that do not correspond to the sequence of dynamic transitions no relay-relay-oscillations-relay are less able or fail to give rise to the formation of spirals.
Proceedings of the National Academy of Sciences 09/1997; 94(17):9153-8. · 9.68 Impact Factor
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ABSTRACT: The effect of intercellular coupling on the switching between periodic behavior and chaos is investigated in a model for cAMP oscillations in Dictyostelium cells. We first analyze the dynamic behavior of a homogeneous cell population which is governed by a three-variable differential system for which bifurcation diagrams are obtained as a function of two control parameters. We then consider the mixing of two populations behaving in a chaotic and periodic manner, respectively. Cells are coupled through the sharing of a common chemical intermediate, extracellular cAMP, which controls its production and release by the cells into the extracellular medium; the dynamics of the mixed suspension is governed by a five-variable differential system. When the two cell populations differ by the value of a single parameter which measures the activity of the enzyme that degrades extracellular cAMP, the bifurcation diagram established for the three-variable homogeneous population can be used to predict the dynamic behavior of the mixed suspension. The analysis shows that a small proportion of periodic cells can suppress chaos in the mixed suspension. Such a fragility of chaos originates from the relative smallness of the domain of aperiodic oscillations in parameter space. The bifurcation diagram is used to obtain the minimum fraction of periodic cells suppressing chaos. These results are related to the suppression of chaos by the small-amplitude periodic forcing of a strange attractor. Numerical simulations further show how the coupling of periodic cells with chaotic cells can produce chaos, bursting, simple periodic oscillations, or a stable steady state; the coupling between two populations at steady state can produce similar modes of dynamic behavior.
Chaos (Woodbury, N.Y.) 11/1992; 2(4):501-512. · 1.80 Impact Factor
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ABSTRACT: We investigate how the introduction of cells oscillating periodically affects the behaviour of a suspension of Dictyostelium discoideum amoebae undergoing chaotic oscillations of cyclic AMP. The analysis of a model indicates that a tiny proportion of periodic cells suffices to transform chaos into periodic oscillations in such suspensions. A similar result is obtained by forcing the aperiodic oscillations by a small-amplitude, periodic input of cyclic AMP. The results provide an explanation for the observation of regular oscillations in suspensions of a putatively chaotic mutant of Dictyostelium discoideum. More generally, the results show how chaos in biological systems may disappear through the coupling with periodic oscillations.
Experientia 07/1992; 48(6):603-6.
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ABSTRACT: We investigate how the introduction of cells oscillating periodically affects the behaviour of a suspension ofDictyostelium discoideum amoebae undergoing chaotic oscillations of cyclic AMP. The analysis of a model indicates that a tiny proportion of periodic cells suffices to transform chaos into periodic oscillations in such suspensions. A similar result is obtained by forcing the aperiodic oscillations by a small-amplitude, periodic input of cyclic AMP. The results provide an explanation for the observation of regular oscillations in suspensions of a putatively chaotic mutant ofDictyostelium discoideum
12. More generally, the results show how chaos in biological systems may disappear through the coupling with periodic oscillations.
Cellular and Molecular Life Sciences CMLS 05/1992; 48(6):603-606. · 6.57 Impact Factor
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Chaos An Interdisciplinary Journal of Nonlinear Science 01/1992; 2:501. · 2.08 Impact Factor
