Qualitative Models in Ecology and their Use in Intelligent Tutoring Systems

We are exploring different approaches to model qualitatively the vegetation dynamics of Brazilian cerrado, in order to assess their suitability to provide the domain-specific knowledge in tutoring systems . Two formalisms, the System of Interpretation of Measurements, Analysis and Observations (SIMAO) and the Qualitative Process Theory (QPT), are compared here in two aspects : capacity for making predictions about the behaviour of a plant population, and the generation of explanations from encoded knowledge . Both SIMAO and QPT-based models can produce similar predictions to those obtained with a numerical model of the same problem . SIMAO provides a useful qualitative algebra to make calculations with heterogeneous variables . However it is not possible to incorporate descriptions of the ecological components nor do dynamic simulations with the SIMAO-based model . On the other hand, QPT allows the encoding of qualitative knowledge and building more detailed models, but does not provide a qualitative algebra for combining empirical values of variables . Both SIMAO and QPT permit the generation of system-based explanations, whereas QPT might be more recommended to generate domain-based explanations . We also discuss the role of different organisational levels and scales of space and time in explaining the behaviour of ecological systems . A combined approach could be advantageous in building tutoring systems . 216 QR-96 1 . Motivation Ecological modelling has been mostly based on mathematical models . Although useful when quantitative data are available and precision is required, this kind of approach is not adequate for representing qualitative and incomplete knowledge about ecosystems . It is also poorlysuited for teaching basic ecological principles : they are difficult to understand, and they lack explicit causal relations among variables . Several approaches have been proposed for modelling and simulation with qualitative knowledge in Qualitative Reasoning (QR) (see Weld & de Kleer 1990) . Some have been applied in building tools to predict the behaviour of ecological systems . They have been used, for example, in management of hydroecological systems (Guerrin 1991 ; Heller et al . 1995), modelling an irrigated crop system (Plant & Loomis 1991), modelling the photosynthesis process (Hunt & Cooke 1994), and applying ecological concepts to social sciences (Kamps & Peli 1995) . Our goal is to model the effects of fire on vegetation dynamics for educational purposes . Initially we are investigating the suitability of QR techniques in producing models that can represent domain specific knowledge in tutoring systems . The work reported here presents a case study in which two different QR approaches were used in modelling the same ecological problem: the System of Interpretation of Measurements, Analyses and Observations (SIMAO) (Guerrin 1991 ; 1992), and the Qualitative Process Theory (QPT) (Forbus 1984) . The objective was to explore their potential to represent entities and relationships, make predictions and then generate explanations about the behaviour of a plant population . These approaches were chosen because SIMAO was developed in an ecological context, whereas QPT, among other traditional ontologies such as the component centred approach (de Kleer & Brown 1984) and the constraint centred approach (Kuipers 1986), is more adequate for representing declarative qualitative knowledge (Salles et al . 1996) . We will present our results in the following way : in Section 2 some characteristics of the ecosystem to be modelled, the Brazilian cerrado, are discussed . A problem is defined and represented as a System Dynamics numerical model, which will be compared to the qualitative models . The following two Sections contain details of qualitative models for the same problem, built according to SIMAO (Section 3) and QPT (Section 4) . Results obtained with them are compared to those obtained in the numerical