Part 1 Cells: From VSLI through machine models to cellular metabolism, Mike Holcombe; developing a logical tool to analyze biological regulatory networks, Rene Thomas and Denis Thieffrey; the computational machinery of the living cell, Rickey Welch; enzymes, automata and artificial cells, Pedro Marijuan; the molecular computer, Chris Winter; computing dendritic growth, Patrick Hmailton. Part 2 Tissues: the brain as a metaphor for sixth generation computing, Michael Arbib; hierarchical search using chemical transmitters in self-organizing pattern recognition architectures, Gail A. Carpenter and Stephen Grossberg; fluid neural networks as a model of intelligent biological systems, Frank T. Vertosick; the immune learning mechanisms - reinforcement, recruitment and their applications, Hughes Bersini and Francisco J. Varela; artificial tissue models, Richard Stark; streaming organizations - the tissue automat, Gershom Zajicek. Part 4 Genetics: evolutionary algorithms - comparison of approaches, Thomas Baeck; artificial evolution and the paradox of sex, Rob Collins; both Wrightian and "parasite" peak shifts enhance genetic algorithm performance in the travelling salesman problem, Brian Sumida and W.D. Hamilton; evolution of emergent co-operative behaviour using genetic programming, John Koza; an evolutionary approach to designing neural networks, Aviv Bergman. Part 5 Ecology: free the spirit of evolutionary computing - the ecological genetic algorithm approach, Yuval Davidor; the ecology of computation, Bernardo A. Huberman; an ecological analysis of a system for detecting nods of the head, Ian Horswill; socio-ecological metaphors and autonomous agents, Geof Staniford. Part 6 Theoretical and conceptual issues: the importance of selectionist systems for cognition, Bernard Manderick; life-like computing beyond the machine metaphor, George Kampis; nature's machine - mimesis, the analog computer and the rhetoric of technology, James Nyce. Conclusion: computing with biological metaphors - some conceptual issues, Ray Paton.
