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Artificial Life, 2009. ALife '09. IEEE Symposium on

Date March 3 2009-April 2 2009

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Displaying Results 1 - 25 of 30
  • [Front cover]

    Publication Year: 2009 , Page(s): c1
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    Freely Available from IEEE
  • [Copyright notice]

    Publication Year: 2009 , Page(s): ii
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    Freely Available from IEEE
  • Table of contents

    Publication Year: 2009 , Page(s): iii - vi
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    Freely Available from IEEE
  • Welcome message

    Publication Year: 2009 , Page(s): vii - x
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    Freely Available from IEEE
  • Dude, where is my sex gene? — Persistence of sex over evolutionary time in cellular automata

    Publication Year: 2009 , Page(s): 1 - 8
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (661 KB) |  | HTML iconHTML  

    We created a simple evolutionary system, F-sexyloop, on a deterministic twelve-state five-neighbour cellular automaton (CA) where self-reproducing loops have the capability of sex. This work was based on the sexyloop which was transformed by adding two new states and new rules. In the F-sexyloop, the loops can carry a sex gene used to facilitate the transfer of genetic material from a loop to another. This gene is analogous to the F factor plasmid in bacterial conjugation which confers the capacity to act as a donor of genetic material (including the gene itself). Therefore, the sex gene could potentially be maintained in the population during evolution or disappear. We show that in a wide variety of cases, the sex gene persists over evolutionary time and is present in the genomes of the dominant species. View full abstract»

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  • Mechanisms affecting the evolution of evolvability

    Publication Year: 2009 , Page(s): 9 - 12
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (461 KB) |  | HTML iconHTML  

    This paper describes a series of simulation experiments based on a model by John W. Pepper [1] on two mechanisms, mutation rate and culling, and their effect on evolvability. The findings suggest that while culling may positively affect the performance of the population, increased culling negatively affects the evolution of the evolvability of the lineage. Similarly, decreasing the mutation rate positively affects performance of the population whereas it negatively affects aspects of evolvability. It suggests that mechanisms affecting evolvability are similar to mechanisms affecting evolution in complex spaces. View full abstract»

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  • A constructivist approach to robot language learning via simulated babbling and holophrase extraction

    Publication Year: 2009 , Page(s): 13 - 20
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (888 KB) |  | HTML iconHTML  

    It is thought that meaning may be grounded in early childhood language learning via the physical and social interaction of the infant with those around him or her, and that the capacity to use words, phrases and their meaning are acquired through shared referential dasiainferencepsila in pragmatic interactions. In order to create appropriate conditions for language learning by a humanoid robot, it would therefore be necessary to expose the robot to similar physical and social contexts. However in the early stages of language learning it is estimated that a 2-year-old child can be exposed to as many as 7,000 utterances per day in varied contextual situations. In this paper we report on the issues behind and the design of our currently ongoing and forthcoming experiments aimed to allow a robot to carry out language learning in a manner analogous to that in early child development and which effectively dasiashort cutspsila holophrase learning. Two approaches are used: (1) simulated babbling through mechanisms which will yield basic word or holophrase structures and (2) a scenario for interaction between a human and the humanoid robot where shared dasiaintentionalpsila referencing and the associations between physical, visual and speech modalities can be experienced by the robot. The output of these experiments, combined to yield word or holophrase structures grounded in the robot's own actions and modalities, would provide scaffolding for further proto-grammatical usage-based learning. This requires interaction with the physical and social environment involving human feedback to bootstrap developing linguistic competencies. These structures would then form the basis for further studies on language acquisition, including the emergence of negation and more complex grammar. View full abstract»

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  • Exploring Empowerment as a Basis for Quantifying Sustainability

    Publication Year: 2009 , Page(s): 21 - 28
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (556 KB) |  | HTML iconHTML  

    Empowerment quantifies the choice available to an agent as the actuation channel capacity. However, not all such choices are sustainable: After some choices, the agent may not be able to return to its original state, or returning there may be costly. In this paper we explore whether empowerment can be adapted to obtain a measure of sustainability. As a straightforward modification, the agent's options is restricted to actions that are reversible within a given time horizon. We furthermore investigate the lengths of return paths and discuss their potential to indicate sustainability. View full abstract»

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  • The impact of communication and memory in hive-based foraging agents

    Publication Year: 2009 , Page(s): 29 - 36
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (429 KB) |  | HTML iconHTML  

    Many hive-based agents, such as some bees, rely on memory and communication to aid in foraging. The benefits of these abilities seem obvious, but it is unlikely that they are beneficial in every environment. In this paper, we present the results of experiments examining the effect that environmental structure can have on the utility of communication and memory for hive-based agents, finding that there are some environments in which they do not contribute substantially to the agents' ability to survive. View full abstract»

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  • Semantic content and pragmatic convention: Emergence through individual advantage in spatialized environments

    Publication Year: 2009 , Page(s): 37 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (842 KB) |  | HTML iconHTML  

    This paper reviews and extends earlier work on the emergence of semantics in spatialized environments of wandering food sources and predators. Communication of any sophistication demands a semantic base, but also relies on conventions of information transfer, of truthfulness, and of relevance. These are pragmatic conventions, formulated in the linguistics literature in terms of H. P. Grice's maxims of quality, quantity, and relation. Simulations offered here show that conditions sufficient for the emergence of simple semantics are also sufficient for the emergence of simple pragmatics. Pragmatic conventions of precisely the type Grice outlines emerge naturally within spatialized networks of individually information-maximizing agentsin an environment of locally significant events. View full abstract»

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  • Using real-time recognition of human-robot interaction styles for creating adaptive robot behaviour in robot-assisted play

    Publication Year: 2009 , Page(s): 45 - 52
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (430 KB) |  | HTML iconHTML  

    This paper presents an application of the Cascaded Information Bottleneck Method for real-time recognition of Human-Robot Interaction styles in robot-assisted play. This method, that we have developed, is implemented here for an adaptive robot that can recognize and adapt to children's play styles in real time. The robot rewards well-balanced interaction styles and encourages children to engage in the interaction. The potential impact of such an adaptive robot in robot-assisted play for children with autism is evaluated through a study conducted with seven children with autism in a school. A statistical analysis of the results shows the positive impact of such an adaptive robot on the children's play styles and on their engagement in the interaction with the robot. View full abstract»

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  • Self-adaptive multi-robot construction using gene regulatory networks

    Publication Year: 2009 , Page(s): 53 - 60
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1064 KB) |  | HTML iconHTML  

    Biological organisms have evolved to perform and survive in a world characterized by rapid changes, high uncertainty, infinite richness, and limited availability of information. Gene regulatory networks (GRNs) are models of genes and gene interactions at the expression level. In this paper, inspired by the biological organisms and GRNs models, a distributed multi-robot self-construction method is proposed. By using this method, a multi-robot system can self-construct to different predefined shapes, and self-reorganize to adapt to dynamic environments. Various case studies have been conducted in the simulation, and the simulation results demonstrate the efficiency and convergence of the proposed method. View full abstract»

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  • Influence of regulation logic on the easiness of evolving sustained oscillation for gene regulatory networks

    Publication Year: 2009 , Page(s): 61 - 68
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1831 KB) |  | HTML iconHTML  

    This paper investigates empirically the influence of regulation logic on the dynamics of two computational models of genetic regulatory network motifs. The gene regulatory network motifs considered in this work consist of three genes with both positive and negative feedback loops. Two forms of fuzzy logic, namely, the Zadeh operators and the probabilistic operators, as well as the summation logic have been investigated. We show that the easiness of evolving sustained oscillation, and the stability of the evolved oscillation depend both on the regulation logic and on the consistency of the regulation on the target gene. View full abstract»

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  • Distinction between types of motivations: Emergent behavior with a neural, model-based reinforcement learning system

    Publication Year: 2009 , Page(s): 69 - 76
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (987 KB) |  | HTML iconHTML  

    In this paper, we analyze the behavior of a simulated mobile robot, which interacts with an initially unknown maze-environment. The robot is controlled by an interactive system that is based on a model building Time Growing Neural Gas (TGNG) algorithm and a homeostatic motivational system, which activates movement preferences and goals within the emergent model structure for behavioral control. We propose to differentiate two types of drives (if not more), which we call location- and characteristics-based drives. We exemplary implement the two types of drives by ldquohungerrdquo and ldquofearrdquo, respectively. Several possible methods of combination of the two drives are investigated through simulation, identifying the combination that lead to the most suitable emergent behavior, such as emergent ldquowall-followingrdquo and ldquohidingrdquo. Moreover, we investigate performance in an ALife-like scenario, in which the robot interacts with several food-dispensers. It is shown that additional behavioral concepts, such as ldquocuriosityrdquo and ldquoinhibition of returnrdquo, can maximize the survival chances of the organism, who maintains maximal safety and keeps its belly full. In conclusion, we propose that the concept of motivation needs to be further differentiated to realize autonomous, life-like robots that are able to optimally satisfy multiple, competing types of motivations by emergent, innovative behavioral patterns. View full abstract»

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  • Developing preferential attention to a speaker: A robot learning to recognise its carer

    Publication Year: 2009 , Page(s): 77 - 84
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3142 KB) |  | HTML iconHTML  

    In this paper we present a socially interactive multi-modal robotic head, ERWIN - Emotional Robot With Intelligent Networks, capable of emotion expression and interaction via speech and vision. The model presented shows how a robot can learn to attend to the voice of a specific speaker, providing a relevant emotional expressive response based on previous interactions. We show three aspects of the system; first, the learning phase, allowing the robot to learn faces and voices from interaction. Second, recognition of the learnt faces and voices, and third, the emotion expression aspect of the system. We show this from the perspective of an adult and child interacting and playing a small game, much like an infant and caregiver situation. We also discuss the importance of speaker recognition in terms of human-robot-interaction and emotion, showing how the interaction process between a participant and ERWIN can allow the robot to prefer to attend to that person. View full abstract»

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  • Enhancing the architecture of interactive evolutionary design for exploring heterogeneous particle swarm dynamics: An in-class experiment

    Publication Year: 2009 , Page(s): 85 - 91
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1198 KB) |  | HTML iconHTML  

    We developed Swarm Chemistry 1.2, a new version of the Swarm Chemistry simulator with an enhanced architecture of interactive evolutionary design for exploring heterogeneous self-propelled particle swarm dynamics. In the new version, each evolutionary operator acts locally and visually to part of the population of swarms on a screen, without causing entire generation changes that were used in earlier versions. This new architecture is intended to represent cognitive actions in human thinking and decision making processes more naturally. We tested the effectiveness of the new architecture through an in-class experiment with college students participating as designers as well as evaluators of swarms. We also measured the effects of mixing and mutation operators to the performance improvement of the design processes. The students' responses showed that the designs produced using the new version received significantly higher ratings from students than those produced using the old one, and also that each of the mixing and mutation operators contributed nearly independently to the improvement of the design quality. These results demonstrate the effectiveness of the new architecture of interactive evolutionary design, as well as the importance of having diverse options of action (i.e., multiple evolutionary operators in this context) in iterative design and decision making processes. This work also presents one of the few examples of human-involved experiments on the statistical evaluation of artificial lifeforms, whose quality (such as ldquolivingnessldquo) would be hard to assess without using human cognition at this point. View full abstract»

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  • Cockroaches, drunkards, and climbers: Modeling the evolution of simple movement strategies using digital organisms

    Publication Year: 2009 , Page(s): 92 - 99
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (810 KB) |  | HTML iconHTML  

    Even the simplest of organisms may exhibit low-level intelligent behaviors in their directed movements, such as in foraging. We used the Avida digital evolution research platform to explore the evolution of movement strategies in a model environment with a single local resource that diffuses to produce a gradient, which organisms have the ability to follow. Three common strategies that evolved, Cockroach, Drunkard, and Climber, exhibit how both environmental constraints and historical contingency play a role in the emergence of intelligent behaviors. The evolved programs are also suitable for use in controllers on robots. View full abstract»

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  • Applying digital evolution to the design of self-adaptive software

    Publication Year: 2009 , Page(s): 100 - 107
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2736 KB) |  | HTML iconHTML  

    As software developers, we strive to create computational systems that are as robust and versatile as biological organisms have evolved to be in nature. We propose a software development methodology capable of producing self-adaptive software, using digital evolution to discover behaviors and optimize solutions. Employing this methodology we present an example behavioral concept from inception to fruition on physical hardware, as a proof of concept of the approach. We evolve environmentally-aware motility behaviors through digital evolution, automatically translate the evolved programs into C code, and compile and load the programs onto mobile robots. View full abstract»

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  • On the properties of artificial development and its use in evolvable hardware

    Publication Year: 2009 , Page(s): 108 - 115
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (694 KB) |  | HTML iconHTML  

    The design of a new biologically inspired artificial developmental system is described in this paper. In general, developmental systems converge slower and are more computationally expensive than direct evolution. However, the performance trends of development indicate that the full benefit of development will arise with larger and more complex problems that exhibit some sort of regularity in their structure: thus, the aim is to evolve larger electronic systems through the modularity allowed by development. The hope is that the proposed artificial developmental system will exhibit adaptivity and fault tolerance in the future. The cell signalling and the system of Gene Regulatory Networks present in biological organisms are modelled in our developmental system, and tailored for tackling real world problems on electronic hardware. For the first time, a Gene Regulatory Network system is successfully shown to develop the complete circuit structure of a desired digital circuit without the help of another mechanism or any problem specific structuring. Experiments are presented that show the modular behaviour of the developmental system, as well as its ability to solve non-modular circuit problems. View full abstract»

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  • Evolution of bilateral symmetry in agents controlled by spiking neural networks

    Publication Year: 2009 , Page(s): 116 - 123
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (752 KB) |  | HTML iconHTML  

    We present in this paper three novel developmental models allowing information to be encoded in space and time, using spiking neurons placed on a 2D substrate. In two of these models, we introduce neural development that can use bilateral symmetry. We show that these models can create neural controllers for agents evolved to perform chemotaxis. Neural bilateral symmetry can be evolved and be beneficial for an agent. This work is the first, as far as we know, to present developmental models where spiking neurons are generated in space and where bilateral symmetry can be evolved and proved to be beneficial in this context. View full abstract»

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  • Ecological approaches to diversity maintenance in evolutionary algorithms

    Publication Year: 2009 , Page(s): 124 - 130
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (446 KB) |  | HTML iconHTML  

    Evolutionary algorithms have shown great promise in evolving novel solutions to real-world problems, but the complexity of those solutions is limited, unlike the apparently open-ended evolution that occurs in the natural world. In part, nature surmounts these complexity barriers with natural ecological dynamics that generate an incredibly diverse array of raw materials for the evolutionary process to build upon, the efficacy of which has been demonstrated in the artificial life system Avida [1]. Here, we introduce a method to integrate ecological factors promoting diversity into an EA using limited resources. We show that populations evolving with this method are able to find and cover multiple niches in a simple string-matching problem, and we analyze the conditions that lead to specialists vs. generalists in this environment. These concepts lay a groundwork for building a more comprehensive ecology-based evolutionary algorithm able to achieve higher levels of complexity. View full abstract»

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  • Emergence and analysis of complex food webs in an individual-based artificial ecology

    Publication Year: 2009 , Page(s): 131 - 138
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2096 KB) |  | HTML iconHTML  

    Food webs are complex networks of trophic interactions in ecological communities that are crucial in creating and maintaining biodiversity, and are prominent examples of biological complexity. In this paper, we present an individual-based model of an artificial ecology demonstrating the emergence of complex food webs through the evolution of rich phenotypes. Individuals are simple structures that map several traits in a nonlinear fashion. Interaction and evolution of these structures leads to the self-assembly of food webs in complex ecological communities. Ecological and network analysis of the evolved artificial ecologies shows remarkable similarities in various patterns known from natural ecological communities. View full abstract»

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  • On the value of simple stoichiometry to ALife simulations using EcoSim

    Publication Year: 2009 , Page(s): 139 - 146
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (617 KB) |  | HTML iconHTML  

    Simulation software is vital to ALife research. It is known that stoichiometry is important for modeling real world ecosystems. However, most currently available ALife simulators ignore stoichiometry mechanics. Of course, not all ALife research is trying to model life as it is found on earth. In this paper, we demonstrate the value of including simple stoichiometry in ALife simulation software. Through extensive simulation results, we show that it is worthwhile even in simulators far removed from modeling real organisms on earth. Including simple stoichiometry allows agents to fill niches in a complex food web instead of all directly competing for the same resources. This increases the adaptability, survivability, robustness, and diversity of the simulated agents. Consequently the simulator is more powerful and will ultimately yield more intelligent agents. View full abstract»

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  • Biomimetic evolutionary analysis: Robotically-simulated vertebrates in a predator-prey ecology

    Publication Year: 2009 , Page(s): 147 - 154
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1487 KB) |  | HTML iconHTML  

    To test adaptation hypotheses about the evolution of animals, we need information about the behavior of phenotypically-variable individuals in a specific environment. To model behavior of ancient fish-like vertebrates, we previously combined evolutionary robotics and software simulations to create autonomous biomimetic swimmers in a simple aquatic environment competing and foraging for a single source of food. This system allowed us to test the hypothesis that selection for improved forage navigation drove the evolution of stiffer tails. In this paper, we extend our framework to evaluate more complex environments and hypotheses. Specifically, we test the hypothesis that predator-prey dynamics and the need for effective foraging strategies, operating simultaneously, were key selection pressures driving the evolution of morphological and sensory traits in early, fish-like vertebrates. Three evolvable traits were chosen because of their importance in propulsion and predator avoidance: (1) the number of vertebrae in the axial skeleton, (2) the trailing edge span of the caudal fin, and (3) the sensitivity of the sensory lateral line. To produce variable offspring, we used a genetic algorithm that rewarded parents with high fitness, allowing them to mate randomly and combine their mutated gametes. Offspring were then instantiated as autonomous embodied robots, the prey. These prey were chased by a non-evolving autonomous predator. Both kinds of robots were surface swimmers. The prey used a control architecture based on that of living fish: a two-layer subsumption architecture with predator escape over-riding steady swimming during foraging. The performance of six different prey robots in each generation was judged with a relative fitness function that rewarded a combination of high speed, rapid escape acceleration, escape responses, and the ability to stay away from the predator while at the same time staying close to the food source. This approach, which we call biomimet- ic evolutionary analysis, shows promise for investigators seeking new ways to test evolutionary hypotheses about biological systems. View full abstract»

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  • Peak analysis for characterizing evolutionary behavior

    Publication Year: 2009 , Page(s): 155 - 162
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3495 KB) |  | HTML iconHTML  

    Evolutionary algorithms (EAs) use a simplified abstraction of biological evolution to interact with a fitness landscape over multiple generations. The traditional approach to exploring evolutionary motivated search relies on performance comparisons of competing designs for a common problem domain. This approach has been useful in developing an intuition of when one mechanism is superior to another. However, this intuition has developed in the absence of a clear understanding of how fitness landscape topology impacts the search process in high-dimensional space, due to the lack of high-dimensional visualization tools. Proposed is a behavior measure derived from a known set of all problem domain optima, which is used as system of landmarks. Using these landmarks, evolutionary system progress can be tracked in the problem domain and characterized with an information theoretic metric. Thus, this technique provides an intuition that takes into account the problem domain topology, allowing the behavior of different algorithm configurations to be compared as they interact with a given topology. View full abstract»

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