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Recommended literature and interesting links for Virtual Life course 2005. Literature Links see the literature page for Virtual life course 2004 (Still working on the literature list for the course...)
also see the general link page
Famous work by Karl Sims in artificial evolution of 3D-based block creatures. This work is discussed frequently by the other authors. Nice video footage (through ftp).
In 1986 Reynolds made a computer model of coordinated animal motion such as bird flocks and fish schools. It was based on three dimensional computational geometry of the sort normally used in computer animation or computer aided design.
The Tierra simulator explores what happens when evolution by natural selection is embedded in the medium of digital computation. Pieces of software compete with each other for CPU time ("energy") and memory ("material resources"). Diverse ecological communities have emerged. These digital communities have been used to experimentally examine ecological and evolutionary processes, e.g. host/parasite density dependent population regulation, evolutionary arms race, and punctuated equilibrium. Tierra is considered to be the first experiments of self-replication in digital media.
PolyWorld is a computational ecology that Larry Yaeger developed to explore issues in Artificial Life. Simulated organisms reproduce sexually, fight and kill and eat each other, eat the food that grows throughout the world, and either develop successful strategies for survival or die.
Echo is a simulation tool developed to investigate mechanisms which regulate diversity and information-processing in systems comprised of many interacting adaptive agents, or complex adaptive systems (CAS). Echo agents interact via combat, trade and mating and develop strategies to ensure survival in resource-limited environments.
The spatial variant of the iterated prisoner's dilemma is a simple yet powerful model for the problem of cooperation versus conflict in groups. The applet below demonstrates the spread of 'altruism' and 'exploitation for personal gain' in an interacting population of individuals learning from each other by experience.
Many neuroevolution methods evolve fixed-topology networks. Some methods evolve topologies in addition to weights, but these usually have a bound on the complexity of networks that can be evolved and begin evolution with random topologies. This project is based on a neuroevolution method called NeuroEvolution of Augmenting Topologies (NEAT) that can evolve networks of unbounded complexity from a minimal starting point. Especially interesting is "Continual Coevolution Through Complexification (2002)"
A new approach to creating intelligence, rooted in Artificial Life and Natural Selection rather than traditional AI. Computational natural selection, in which the phenotype to fitness mapping is an emergent property of the evolving environment and competition is biotic rather than abiotic, is a paradigm that aims towards the creation of open-ended evolutionary systems. Within such an environment, increasingly complex behaviours can emerge.
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