Since 1990 we have been involved in modeling decision-making, particularly in fish and plankton. Much of this work is based on a theoretically derived model for visual range of aquatic organisms (Aksnes & Giske 1993, Aksnes & Utne 1997), which again has allowed calculations of feeding rates and predation risks (Giske & al. 1994, Fiksen & al. 2002).

We have been using Life History Theory (Aksnes & Giske 1990, Giske & Aksnes 1992, Salvanes & al. 1994, Giske & Salvanes 1995, Eiane & al. 1998), Game Theory (Giske & al. 1997) and State-Dependent Optimization (Giske & al. 1992, Rosland & Giske 1994, 1997, Fiksen & Giske 1995, Fiksen 1997, Rosland 1997, Fiksen & Carlotti 1998, Kirby & al. 2000) to model both short-term and life-history decisions. More recently, we have been using Genetic Algorithms to evolve adaptive behaviors in Individual-Based Models, either directly as life-history decision genes, neural networks of brains, or decisions coming out from the feelings of the individuals. We have also performed field and lab studies to test assumptions in the models.