Topics 1. Fundamental representation issues   • Management of spatio/temporal knowledge (spatio/temporal reasoning, extension of GIS capabilities, reasoning across several levels of temporal or spatial granularity).   • Management of uncertainty and imprecision (fuzzy logic, belief functions, Bayesian networks, qualitative reasoning).   • Modeling of Multi-agent systems (population modeling, distributed problem solving). 2. Tools, techniques, algorithms   • Use of emerging technologies (neural network, genetic algorithms, fuzzy control, constraint satisfaction, case-based reasoning).   • Fusion of multiple sources of information (in particular for interpretation systems).   • Rise of AI in simulation tools (discrete event systems, use of advanced representation capabilities, qualitative/quantitative simulation).   • Integration/combination of AI approaches with other approaches. 3. Applications and practical issues   • Successful or novel AI decision support approaches for planning, scheduling, control, monitoring, prediction or diagnosis problems in agriculture and related domains.   • Commercialized and routinely used AI-based systems, in particular expert and knowledge-based systems (in laboratories, extension services, farms).   • Critical analysis of project failures.   • Validation issues for AI-based decision support systems.   • Intelligent information systems, and web intelligence.