In RoboCup-98, sparrows team worked hard just to get both a simulation and a middle size robot team to work and to successfully participate in a major tournament. For this year, we were in a better position to start some more serious research work. Aside of improvements in the robot hardware and an extension of the vision processing capabilities, we implemented a more complete version of our soccer agent architecture and made some progress in the areas player localization, environment modelling, and basic playing skills. For the latter, we started to apply learning techniques. 1 Motivation and Research Goals ULM-Sparrows is a research effort seeking to investigate and solve open problems relevant to both the RoboCup Challenge [KAK+ 97] and a local interdisciplinary research effort called SMART [PK97]1 . Some research issues of particular interest to our team include skill learning in continuous domains, adaptive spatial modeling of highly dynamic environments, and emergent multiagent...