Our main interest is in building biologically-inspired systems ('brains', 'bodies'), combining various time scales: behaviour, development and evolution. Our research lies at the intersection of artificial life (including artificial embryology), evolutionary biology and computational neuroscience. We are developing artificial life software platforms and tools for the analysis of evolution of genomes, evolution and complexity of gene regulatory networks, and for the analysis of biological diversity.
Our software platforms are based on the principle of genome-physics interaction in shaping the morphogenesis and on the paradigm of indirect genotype-phenotype relationship (evolvable and efficient encoding of the features of an organism). Such a platform will allow to model the coevolution of the shape of the multicellular organism (“the body”) and the way its behaviour is controlled (“the mind”). We believe that truly embodied intelligence can only be possible when mind-body co-evolution is allowed.
The interaction between the organisms and their environment depends on the physical features of the environment: the particular laws of physics, such as gravity, friction/viscosity and diffusion of substances. The environment shapes the biological organisms at three temporal scales: (i) the long-term evolutionary scale (a particular genome is shaped by the environment of the organism's ancestors), (ii) the intermediate scale of morphogenesis (development) and (iii) the short-time scale of behaviour, the interaction of the organism with its environment as it obtains resources in order to reproduce.
Building a system that integrates various time scales requires careful design in which biological realism has to be balanced with computational limitations. Such a system will be a very important contribution to the field of artificial life and theoretical biology, allowing the exploration of important hypotheses in the fields of evolutionary biology, developmental biology, systems biology, and also cognitive science and theoretical neurobiology. Specific research questions include the investigation of robustness of developed networks, statistical properties of the biologically-inspired networks, evolution of cooperation between the cells, evolution of symmetry breaking and patterning mechanisms during development of multicellular bodies, and emergence of intelligent behaviour.