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The Impact of Fear on Eating and Fleeing in Virtual Flocking Animals

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The Impact of Fear on Eating and Fleeing in Virtual Flocking Animals Having it both ways – the impact of fear on eating and fleeing in virtual flocking animals Carlos Delgado Mata Bonaterra University, Mexico Ruth Aylett Heriot-Watt University, UK Abstract ple a sheep that experiences an anxiety-inducing stimulus may carry on grazing but bunch up more tightly with the The paper investigates the role of an affective sys- rest of the flock. A second is to switch behaviours: a sheep tem as part of an ethologically-inspired action- that experiences a threatening stimulus inside its flight zone selection mechanism for virtual animals in a 3D will flee. A third function is to avoid dithering between interactive graphics environment. It discusses the competing behaviours by adding weight to one of them integration of emotion with flocking and grazing [Blumberg 1994], and a fourth and related function is to behaviour and a mechanism for communicating sustain a selected behaviour for an appropriate interval – a emotion between animals. We develop a metric for fleeing animal can typically no longer perceive the threat- analyzing the collective behaviour of the animals ening predator, but fear keeps it running, in effect acting and its complexity. We show that emotion reduces like a cheap short-term memory. the complexity of behaviour and thus mediates However flocking animals do not behave merely as iso- between individual and collective behaviour. lated individuals, they engage in the collective behaviour known as flocking. The seminal work of Reynolds [1987] 1 Introduction showed that flocking behaviour does not require a complex For much of its history, the field of Artificial Intelligence internal architecture but can be produced by a small set of (AI) had stressed reasoning and logic and almost ignored the simple rules. In his model of so-called boids, every individ- role of emotion and intuition in intelligent behaviour. Min- ual (boid) tries to fulfil three conditions: cohesion or flock sky (1985) was one of the first to emphasise the importance centring (attempt to stay close to nearby flockmates), align- of emotion for Artificial Intelligence. Since then, affective ment or velocity matching (attempt to match velocity with systems for embodied autonomous agents, whether robotic nearby flockmates), and separation or collision avoidance or graphical, have become an expanding research area. One (avoid collisions with nearby flockmates). Flocking is thus a may divide approaches roughly into two: low-level ac- collective emergent behaviour. counts, focusing on animals in general, sub-symbolic be- This approach has produced sufficiently believable col- havioural architectures and neuro-physiologically inspired lective behaviour to be used for stampedes in a number of [Velasquez 1997, Canamero 1998], and high-level accounts, animated films. Nevertheless, mammals do in fact have a focusing on humans, symbolic appraisal-driven architec- complex internal architecture, unlike social insects, and a tures, and inspired by cognitive science [Ortony et al 1988, wide range of individual behaviours: a motivation for this Gratch et al 2001]. In this work, we concentrate on a low- work was to reconcile the generation of collective behaviour level account, applied to exemplary flocking mammals by a small set of rules with the more complex agent archi- (sheep, deer), and demonstrate the role of fear as a social tecture required for a mammalian behaviour repertoire. regulator between individual and group behaviour. We take An important behaviour in the ungulate repertoire is the set of ‘primitive emotions’ for which facial expressions grazing, requiring spatial orientation behaviours. Two such are recognized across cultures in humans [Eckman 1982] as mechanisms of particular relevance are described in Lorenz a plausible set for other mammals, namely: anger, fear, dis- [1981]. The first, kinesis can be summarized as a reactive gust, surprise, happiness and sadness, and examine how rule of slowing down when encountering favourable condi- they can be integrated into an ethologically-based action- tions and speeding up for unfavourable ones: this can also selection mechanism. be related to escape behaviour. However most organisms do An evolutionary approach to emotions would argue that not move in an absolutely straight line; when orienting to for affective systems to have developed and remained under favourable localities: the effect of kinesis can be improved the pressure of selection, they must play a definite func- by increasing the angle of the random deviations from the tional role within the overall architecture of animals. A straight line, and these are inherent to locomotion in any number of such functions can be identified in relation to the case. By these means, the organism is kept in the desirable selection of actions. One is to modify behaviour: for exam- environment longer and is made to exploit an increased part of its area, especially relevant to grazing. This second en- of the system/variables, the inputs associated to them, a hanced mechanism is termed klinokinesis and it is found in weight, and a function (acting as a filter, in most cases a grazing mammals, as well as in swimming protozoa and sigmoid) which in turn generated a feed-forward hierarchy higher crustacea. This represents an important example of like the one described by Tyrrell [1993] individually-oriented behaviour which conflicts with the rule-set for flocking. 2.1 Communicating emotion Taking the position that emotion partly functions as a com- 2 An ethologically inspired action-selection munication mechanism, a novel feature of this work is that mechanism the perceptual component has been designed to support the communication of emotion among conspecifics. In the real The work discussed here has been implemented with simu- world, emotional transmission is almost certainly multi- lated sheep and deer in a 3D interactive virtual environment. modal, with certain modes such as the perception of motion In order to test the hypothesis that an affective system can being particularly difficult to model. Thus we have limited act as a regulating mechanism between individual and social ourselves for now to a single mode, and the one we have behaviour, an ethologically-motivated architecture was de- chosen is pheromones, perceived by a virtual olfaction sen- veloped for the virtual animals. sor. The basic task of a virtual animal brain has often been Recent experiments [Grammer 1993] have shown that split into the three sub-tasks of perception (sensing the envi- mammals, including humans, emit pheromones through ronment and interpreting the sensory signals to provide a apocrine glands as an emotional response, and as means to high-level description of the environment), action selection communicate that state to conspecifics, who can adapt their (using the perceptual and emotional inputs to decide which behaviour accordingly; research has found that odours pro- of the animal's repertoire of actions is most suitable at that duce a range of emotion responses in animals, including moment) and motor control (transforming the chosen action humans [Izard1993]. This is adaptively advantageous be- into a pattern of "physical" actions to produce the animation cause olfaction is part of the old smell-brain which can gen- of the animal). To this we add a fourth subtask: generating erate fast emotional responses, that is without the need of emotions (affecting the behaviour of the animals, exempli- cognitive processes. fied by the conspecifics flight-flocking), Figure 1 shows a Grammer [1993] argues that every living creature has a detailed diagram of the designed architecture developed as a distinctive molecular signature that can be carried in the result, and the next sections describe its components. wind, variously showing it to be nutritious, poisonous, sex- While not claiming neurophysiological accuracy, the ar- ual partner, predator or prey. Neary [2001] points out that chitecture splits its overall functionality across biologically- sheep, particularly range sheep, will usually move more plausible subsystems. Thus the module hypothalamus is readily into the wind than with the wind, allowing them to used to store the drives (for example, hunger), the sensorial utilise their sense of smell. cortex stores sensor data, the amygdala contains the emo- Our architecture models the exteroceptors used by real tional systems such as Fear, Joy and Anger, and Basal Gan- animals to detect the presence of chemicals in the external glia contains the hierarchical mechanism for selecting ac- environment as a virtual nose. An environmental simulator tions, similar to those described by ethologists. Each of the has been developed: its tasks include changing the tem- listed modules is defined in XML giving the name of each perature and other environmental variables depending on the time of day and on the season, using statistical historical data. An alarmed animal sends virtual pheromones to the environmental simulator and they are simulated using the free expansion gas formula in which the volume depends on the temperature and altitude (both simulated environmental variables). The expansion of the pheromone cloud at timestep=9 can be seen in a graphical environment in Figure 6 below. To compute the distribution of the pheromones a set of particles has been simulated using the Boltzmann dis- tribution formula: Here m is the pheromone mass; g is the gravity; y is the altitude; kb is the Boltzmann number; T is the temperature; n0 is N/V where N is the number of molecules exuded from the apocrine gland (related to the intensity of the emotion) and V is the volume. The virtual nose detects pheromones from a threshold of 200.10-16 reflecting values taken from FIGURE 1: Complete architecture the relevant literature. 2.2 Action-selection mechanism The problem of action selection is that of choosing at each 2.3 The flocking mechanism moment in time the most appropriate action out of a reper- toire of possible actions. The process of making this deci- The basic Reynolds rules of cohesion, alignment and sepa- sion takes into account many stimuli, including in this case ration have been extended with an additional rule (escape) the animal's emotional state.
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