Search

International audience; A spectroscopic investigation on the effect of Ce co-doping in fluoride KYF:Pr crystals is presented. In particular spectroscopic measurements of three different samples of KYF crystal doped with 0.3at% Pr and co-doped with 0at%, 0.17at% and 0.3at% Ce are discussed. Details on the growth of the crystals are also reported. Measurements were performed in the temperature range 10 - 300 K. Fluorescence and lifetime measurements have shown a cross relaxation between P - D levels of Pr and 2F -F of Ce. Data exhibit that this effect is strictly related to the Cerium concentration.

Models proposed within the literature of motor control have polarised around two classes of controllers which differ in terms of controlled variables: the Force-Control Models(FCMs), based on dynamic control, and the Equilibrium-Point Models (EPMs), based on kinematic control. This paper proposes a bioinspired model which aims to exploit the strengths of the two classes of models. The model is tested with a 3D physical simulator of a 2DOF-controlled arm robot engaged in a reaching task which requires the production of curved trajectories to be solved. The model is based on an actor-critic reinforcementlearning algorithm which uses neural maps to represent both percepts and actions encoded as joint-angle desired equilibrium points (EPs), and a noise generator suitable for fine tuning the exploration/exploitation ratio. The tests of the model show how it is capable of exploiting the simplicity and speed of learning of EPMs as well as the flexibility of FCMs in generating curved trajectories. Overall, the model represents a first step towards the generation of models which exploit the strengths of both EPMs and FCMs and has the potential of being used as a new tool for investigating phenomena related to the organisation and learning of motor behaviour in organisms.

Organisms, and especially primates, are able to learn several skills while avoiding catastrophic interference and enhancing generalisation. This paper proposes a novel hierarchical reinforcement learning (RL) architecture with a number of features that make it suitable to investigate such phenomena. The proposed system combines the mixture of experts architecture with the neural-network actor-critic architecture trained with the TD() reinforcement learning algorithm. In particular, responsibility signals provided by two gating networks (one for the actor and one for the critic) are used both to weight the outputs of the respective multiple (expert) controllers and to modulate their learning. The system is tested with a simulated dynamic 2D robotic arm that autonomously learns to reach a target in (up to) three different conditions. The results show that the system is able to appropriately allocate experts to tasks on the basis of the differences and similarities among the required sensorimotor mappings.

Recently the computational-neuroscience literature on animals' learning has proposed some models for studying organisms' decisions related to the energy to invest in the execution of actions (\vigor"). These models are based on average reinforcement learning algorithms which make it possible to reproduce organisms' behaviours and at the same time to link them to speciØc brain mechanisms such as phasic and tonic dopamine-based neuromodulation. This paper extends these models by explicitly introducing the dynamics of hunger, driven by energy consumption and food ingestion, and the eÆects of hunger on perceived reward and, consequently, vigor. The extended model is validated by addressing some experiments carried out with real mice in which reinforcement schedules delivering lower amounts of food can lead to a higher vigor compared to schedules delivering larger amounts of food due to the higher perceived reward caused by higher levels of hunger.

An influential hypothesis of developmental psychology states that, in the first months of their life, infants perform exploratory/random movements ("motor babbling") in order to create associations between such movements and the resulting perceived effects. These associations are later used as building blocks to tackle more complex sensorimotor behaviours. Due to its underlying simplicity, motor babbling might be a learning strategy widely used in the early phases of child development. Various models of this process have been proposed that focus on the acquisition of reaching skills based on the synchronous association between the positions of the postures that cause them. This research tries to understand, on a computational basis, if the principles underlying motor babbling can be extended to the acquisition of behaviours more complex than reaching, such as the execution of non-linear movement trajectories for avoiding obstacles or the acquisition of movements directed to grasp objects. These behaviours are challenging for motor babbling as they involve the execution of movements, or sequences of movements, in time, and so they cannot be learned on the basis of simple synchronous associations between their neural representations and perceptive neural representations. The paper aims to show that infants might still use motor babbling for the development of these behaviours by overcoming its time-limits on the basis of complementary mechanisms such as Pattern Generators and innate reflexes. The computational viability of this hypothesis is demonstrated by testing the proposed models with a 3D simulated dynamic eye-arm-hand robot working on a plane.

Behavioural and brain imaging evidence has shown that seeing objects automatically evokes "affordances", for example it tends to activate internal representations related to the execution of precision or power grips. In line with this evidence, Tucker and Ellis found a compatibility effect between object size (small and large) and the kind of grip (precision and power) used to respond whether seen objects were artefacts or natural objects. This work presents a neural-network model that suggests an interpretation of these experiments in agreement with a recent theory on the general functions of prefrontal cortex.

We report the successful growth and the laser cooling results of Yb3+-doped single fluoride crystals. By investigating the mechanical and thermal properties of Yb-doped BaY2F8 and LiYF4 crystals and using the spectroscopic data we collected from our samples, the theoretical and experimental cooling efficiency of fluoride crystals are evaluated and compared with respect to those of ZBLAN. Two different methods, a thermal camera and a fluorescence intensity ratio technique, have been used to monitor the temperature change of the samples. The temperature change is clearly exponential, as expected from theory, and the temperature drops are 6.3 K and 4 K for Yb:LiYF4 and Yb:BaY2F8 respectively in single-pass configuration, corresponding to a cooling efficiency of about 2% and 3%. This last value is slightly larger than that observed in Yb-ZBLAN in similar experimental condition.

One of the most influential principles of motor development theory, the circular-reaction hypothesis, states that infants perform exploratory movements to acquire efferent-reafferent associations later used to perform goal directed behavior. All models proposed so far to specify this principle lack biological plausibility under some respects. This work proposes a model that starts to overcome these limitations. In particular, the model aims to show that overcoming such limitations in an integrated fashion can shed new light on so-far overlooked phenomena of motor development. This goal is pursed by showing how the model develops biologically plausible connections and movement smoothing mechanisms as emergent outcomes of the interplay between its various biologically-plausible features: a dynamic arm with realistic parameters, an equilibrium-point muscle model, a leaky-neuron neural controller based on population codes, and a Hebb learning rule.

We describe simulations of groups of agents that have to reach a target in a two dimensional environment, the performance criterion being the time taken by the last agent to reach the target. If the target is within a given distance from the agent, the agent moves towards the target; otherwise it moves randomly. The simulations contrast groups with and without a leader, where a leader is a member of the group which other members of the group follow as it moves through the environment. We investigate three factors that affect group performance: (1) group size; (2) the presence or absence of an individual agent with the ability to detect targets at a greater distance than those 'visible' to its companions; (3) the existence of a communication network among group members. The results show that, in groups without communication, leaders have a beneficial effect on group performance, especially in large groups and if the individual with better than average sensory capabilities is the leader of the group. However, in situations where group members can communicate, these results are reversed, with leaders being detrimental, rather than beneficial, to group performance

In this paper we will use formal models and computer simulations to explore some consequences of adding inter-group interactions for the cultures of two previously separated groups.

Santa Fe' Institute Series

Cambridge, MA: MIT press

The question "What drove foragers to farm?" has drawn answers from many different disciplines, often in the form of verbal models. Here, we take one such model, that of the ideal free distribution, and implement it as an agent-based computer simulation. Populations distribute themselves according to the marginal quality of different habitats, predicting settlement patterns and subsistence methods over both time and space. Our experiments and our analyses thereof show that central conclusions of the ideal free distribution model are reproduced by our agent-based simulation, while at the same time offering new insights into the theory's underlying assumptions. Generally, we demonstrate how agent-based models can make use of empirical data to reconstruct realistic environmental and cultural contexts, enabling concrete tests of the explanatory power of anthropological models put forward to explain historical developments, such as agricultural transitions, in specific times and places.