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We present a new self-reproducing cellular automaton capable of construction and computation beyond self-reproduction. Our automaton makes use of some of the concepts developed by Langton for his self-reproducing automaton, but provides the added advantage of being able to perform independent constructional and computational tasks alongside self-reproduction. Our automaton is capable, like Langton's...
In this work we analyze different existing cellular automata capable of reproducing, and conclude that reproduction in those models is attained as a fixed point of the more general operation of construction, instead of being founded as a higher level specialized mechanism. Thus reproduction becomes a very unstable property and this fact is an obstacle in the aim of studying it together with other...
This paper discusses the complexities of designing and evaluating Alife learning systems using physical robots interacting in complex, dynamic environments. We use the learning data from two different implemented multi-robot learning systems to illustrate the difficulties with traditional “objective” methods of evaluation. We then describe the methods we used to evaluate the behavior of such learning...
We are providing a simulation model of the echolocation phenomenon and biological sonar of bats during night flight. Our simulations are based on stationary or mobile obstacle avoidance and prey recognition (moths) by the artificial bats. Echolocation is the navigation system adopted by bats, dolphins, killer whales, as well as the majority of autonomous mobile robots (AMR). To begin with,...
One of the fundamental abilities required in autonomous mobile agents is the one of homing. Natural agents like ants solve this problem by mainly using dead-reckoning mechanisms within an egocentric frame of reference. Here we present a biologically inspired orientation mechanism, an adaptive light compass, that was used for homing in ”Myrmix”, a mobile robot equipped with infrared and ambient light...
This paper describes a formal model of a dynamic and egocentric memory used for predicting the evolution of a local function of proximity. This model is represented by a polar function able to trig the reactive behaviors (reflex actions for collision avoidance) of a planar mobile robot. It also addresses the implementation of this model with an artificial neural network first on a simulator that has...
This paper describes a vehicle to perform a simple task using a decision control composed of a behavior hierarchy. First the model is presented. It is based on two fundamental components: the behavior module defining how each behavior element is implemented; and the blocker which is the basic component of the arbitration system, responsible for behavior selection. Behavior modules are composed of...
Artificial evolution can operate upon reconfigurable electronic circuits to produce efficient and powerful control systems for autonomous mobile robots. Evolving physical hardware instead of control systems simulated in software results in more than just a raw speed increase: it is possible to exploit the physical properties of the implementation (such as the semiconductor physics of integrated circuits)...
In psychology classification is studied as a separate cognitive capacity. In the field of autonomous agents the robots are equipped with perceptual mechanisms for classifying objects in the environment, either by preprogramming or by some sorts of learning mechanisms. One of the well-known hard and fundamental problems is the one of perceptual aliasing, i.e. that the sensory stimulation caused by...
In a multilegged walking system, the legs, when in stance mode, have to cooperate to propel and support the body and, at the same time, to avoid unwanted forces across the body. As a simple method to control the joint movement, we propose to use local high-pass filtered positive feedback. This does not only make redundant the determination of equations for coordinate transformation, but is also robust...
The success of the behaviour-based approach to designing robot control structures has largely been a result of the bottom-up development of a number of fast, tightly coupled control processes. These are specifically designed for a particular agent-environment situation. The onus is on the designers to provide the agent with a suitable response repertoire using their own knowledge of the proposed agent-environment...
In this paper we present the interactive model of knowledge representation and examine its relevance to behavior-based robot control. We show how the interactivist position that representation and motivation are different aspects of the same underlying ontology of interactive dynamic systems emerges within the framework of our Behavior-Network architecture. The behavior-network architecture consists...
The pitfalls of naive robot simulations have been recognised for areas such as evolutionary robotics. It has been suggested that carefully validated simulations with a proper treatment of noise may overcome these problems. This paper reports the results of experiments intended to test some of these claims. A simulation was constructed of a two-wheeled Khepera robot with IR and ambient light sensors...
This paper studies the essential dynamical structure that arises in two different classes of learning of the sensory-based navigation, namely skill-based learning and model-based learning. In skill-based learning a robot learns navigational skills for a fixed navigational task such as homing, while in model-based learning a robot learns a model of the environment, then conducts planning on the model...
Societies are formed as collaborative structures to execute tasks that are not possible or are otherwise difficult for individuals alone. There are many types of biological societies, but societies formed by machines or robots are still rare. The concept offers, however, interesting possibilities especially in applications where a long term fully autonomous operation is needed and/or the work to be...
The Prisoner's Dilemma is a widely employed metaphor for problems associated with the evolution and maintenance of cooperative behaviour. Here we outline a new approach, in which players — who are either pure cooperators or pure defectors — interact with neighbours in some spatial array. Such “spatial games” avoid problems associated with earlier work based on individual strategies, such as “tit-for-tat”,...
This paper describes our most recent investigations into aggressive communication. We perform experiments in a simple synthetic ecology, in which simulated animals (animats) are in competition over food. In the first experiment, each animat has an evolved signaling strategy — the degree to which that animat ‘bluffs’ about its aggression level. The form of artificial evolution used features no explicit...
A major difficulty in understanding how an insect society functions is to be able to deduce collective activity from individual behaviour. Collective behaviour is not just the sum of each individual's behaviour, as patterns can emerge at the level of the society resulting from interactions between individuals or between individuals and the environment. A particular question concerns the organisations...
We present a model inspired by task switching of ants in a colony. The model consists of a system composed of many identical ants. Each ant has a finite number of internal states. An ant's internal state changes either by interaction with the environment or by interaction with another ant. Analyzing the model's dynamics, we prove it to be computationally complete. This gives us a new perspective on...
A hierarchy of cognitive agents is presented here in order to insist on the importance of interactions within a society of self teaching agents. In particular, this paper focuses on mimicry as the interaction mechanism of choice for hedonic agents. The dynamics of this mimetic type of interaction is studied both theoretically and by simulation. It leads to the coevolutionary dynamics best explained...
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