The Research Excellence award is IJCAI's highest honor. It is given to an individual how has made a range of lasting contributions to the theory and practice of our field. It is a great pleasure for me to introduce this year's Research Excellence Award recipient, Professor Nils Nilsson. Nils is recognized for his pioneering work in the use of heuristics, representations, and techniques for building AI systems capable of planning and acting in the real world. I would like to take this opportunity to provide some further background on Nils's contributions. Most of these are widely known in the field. However, some of you may be less familiar with of his earlier work on machine learning and neural networks. In 1965, Nils published a research monograph dealing with the theoretical foundations of neural nets and machine learning, called "Learning Machines". This monograph was recently republished. What is surprising about this text is that it provides a clear introduction to many of issues that lie at the core of recent developments in machine learning. The text is in fact an excellent starting point for students who want to get a better understanding of machine learning research. It is remarkable that a scientific text written almost 40 years ago can still provide such an up-to-date perspective on the key issues of a rapidly moving field. The Learning Machines monograph is the first example of Nils's unique ability to get to the core of scientific problems and to use a concise mathematical formulation to capture the key questions. Nils received the 1995 IEEE Neural Networks Council Pioneer Award in recognition of his contributions. In the late 60s and early 70s, Nils and his colleagues at SRI, started their work on Shakey, the robot. This was the first project aiming at a full integration of AI techniques, combining sensing, acting, planning and reasoning. This work led to several core advances in the field. For example, Nils, together with Hart and Raphael, developed the A* search algorithm. Because of its general applicability and effectiveness, A* search is today one of the most widely used AI techniques. In addition, this work led to a large literature analyzing properties of and variations on A* search. Another seminal contribution coming out of the Shakey robot project was STRIPS planning. This work was done jointly with Richard Fikes. It is one of the earliest examples of how one may have to limit the expressiveness of a representation language in order to obtain a practically feasible AI system. The STRIPS formalism is very much alive today. The representation captures the core of the planning problem and is the basis of planning formalisms used in practically all modern planning systems. Moreover, the heuristic search techniques, introduced with the STRIPS planner, have recently been re-discovered in the latest heuristic search planners, which are now able to generate plans with several hundreds of steps in matter of seconds. It is fair to say that the STRIPS paper has been one the most influential papers in all of planning research. One characteristic of Nils's research career is that he moves with ease between topics. After his work on Shakey, planning, and search, Nils turned his attention to probabilistic reasoning. First in the context of the PROSPECTOR system and later in terms of combining probabilistic and logical representations. This work became part of the foundations of one of the most actives areas of current AI involving probabilistic representations and reasoning. In his latest research, Nils is developing a new fully integrated formalism for sensing, planning, and acting, in his work on teleo-reactive programs. One recurring theme throughout Nils's career has been an emphasis on basic research questions and issues, while keeping the overall goals of AI in mind. His lecture in the mid 90s entitled "Eye on the Prize" laid out a plan for returning to an integrated vision of general purpose programs that reach human-like competence. It is clear from Nils's own contributions that pursuing such ambitious goals can have great scientific payoffs. In addition to his scientific contribution, Nils has contributed to our field through a range of professional leadership positions, most notably President of AAAI, Director of SRI, and Department Chair at Stanford. Nils is of course also well-known for a number of seminal AI text books. These text have educated several generations of AI researchers. The clarity and rigorous treatment of the various core problems in AI and AI techniques has directly contributed to the growth of our field in terms of scientific rigor and sophistication. In summary, it would be difficult to find another individual with such an outstanding record of scientific achievements, research leadership, and educational excellence. It is therefore my pleasure to present you Nils Nilsson. Nils will talk on "Adventures in Artificial Intelligence".