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Numerical recipes: the art of scientific computing
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Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Intelligence as adaptive behavior: an experiment in computational neuroethology
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Simulation of adaptive behavior in animats: review and prospect
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The motion dynamics of snakes and worms
SIGGRAPH '88 Proceedings of the 15th annual conference on Computer graphics and interactive techniques
Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back
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Interaction and intelligent behavior
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Automated learning of muscle-actuated locomotion through control abstraction
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Improv: a system for scripting interactive actors in virtual worlds
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Where to look? Automating attending behaviors of virtual human characters
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AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
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Visual modeling for computer animation: Graphics with a vision
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Creatures: Entertainment Software Agents with Artificial Life
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Action Reaction Learning: Automatic Visual Analysis and Synthesis of Interactive Behaviour
ICVS '99 Proceedings of the First International Conference on Computer Vision Systems
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VW '00 Proceedings of the Second International Conference on Virtual Worlds
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VW '00 Proceedings of the Second International Conference on Virtual Worlds
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KI '01 Proceedings of the Joint German/Austrian Conference on AI: Advances in Artificial Intelligence
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Artificial Life
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AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
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ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
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IVA'06 Proceedings of the 6th international conference on Intelligent Virtual Agents
Implementation of the avoidance algorithm for autonomous mobile robots using fuzzy rules
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Evolving creatures in virtual ecosystems
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This article develops artificial life patterned after animals as evolved as those in the superclass Pisces. It demonstrates a virtual marine world inhabited by realistic artificial fishes. Our algorithms emulate not only the appearance, movement, and behavior of individual animals, but also the complex group behaviors evident in many aquatic ecosystems. We model each animal holistically. An artificial fish is an autonomous agent situated in a simulated physical world. The agent has (a) a three-dimensional body with internal muscle actuators and functional fins that deforms and locomotes in accordance with biomechanic and hydrodynamic principles; (b) sensors, including eyes that can image the environment; and (c) a brain with motor, perception, behavior, and learning centers. Artificial fishes exhibit a repertoire of piscatorial behaviors that rely on their perceptual awareness of their dynamic habitat. Individual and emergent collective behaviors include caudal and pectoral locomotion, collision avoidance, foraging, preying, schooling, and mating. Furthermore, artificial fishes can learn how to locomote through practice and sensory reinforcement. Their motor learning algorithms discover muscle controllers that produce efficient hydrodynamic locomotion. The learning algorithms also enable artificial fishes to train themselves to accomplish higher level, perceptually guided motor tasks, such as maneuvering to reach a visible target.