Using Domain Knowledge on Population Dynamics Modeling for Equation Discovery

Abstract

State of the art equation discovery systems are concerned with the empirical approach to modeling of physical systems, where none or a very limited portion of the expert knowledge about the observed system is used in the modeling process. In this paper, we propose a formalism for integration of the population dynamics modeling knowledge into the process of equation discovery. The formalism allows the encoding of a high-level domain knowledge accessible to human experts. The encoded knowledge can be automatically transformed into the operational form of context dependent grammars. We present an extended version of the equation discovery system L agramge that can use these context free grammars. Experimental evaluation shows that the integration of domain knowledge in the process of equation discovery considerably improves the efficiency and noise robustness of L agramge .