Happy Silver Anniversary, Artificial Intelligence! Twenty five years is not long in the history of a science--long enough to achieve, short enough to remember. Your esteemed founders are still around -- vigorous, not so young anymore. Out of the cybernetics you came, and information-theoretic psychology. You were born in the early days of modern computing, on hot, bulky hardware with names few now remember, like JOHNNIAC; in strange and wonderful software called list structures, with stacks you could "push down" and "pop-up," bearing arcane acronyms like IPL and FLPL. Time-sharing? One signed up on the schedule. Interaction? One pushed keys on the console teleype or panel.

I am absolutely delighted to be able to join in this morning to offer my reflections on the occasion of the official beginning of the Robotics Institute. Beginnings are full of promise and potential. This one is no exception. What the Robotics Institute will become -- what effects it will have, both witting and unwitting -- are for the future to tell. What we all have now is a sense of adventure and anticipation.

Proc. AAAI-80, pp. 170-73.

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This approach leads to an infinite sequence of algorithms I. Surface Models

Our purpose in studying natural language understanding in conjunction with problem solving is to bring together the constraints of what formal representation can actually be obtained with the question of what knowledge is required in order to solve a wide range of problems in a semantically rich domain. We believe that these issues cannot sensibly be tackled in isolation. In practical terms we have had the benefits of an increased awareness of common problems in both areas and a realisation that some of our techniques are applicable to both the control of inference and the control of parsing. Early work on solving mathematical problems stated in natural language was done by Bobrow (STUDENT - (i]) and Chamiak (CARPS - [5]). However the rudimentary parsing and simple semantic structures used by Bobrow and Charniak are inadequate for any but the easiest problems. Our intention has been to build on B/RG Chris This work was supported by SRC grant number 94493 and an SRC research studentship for Mellish.

Distributed systems are multi-processor information processing systems whichdo not rely on the central shared memory for communication. The importanceof distributed systems has been growing with the advent of "computer networks"of a wide spectrum: networks of geographically distributed computers at one end,and tightly coupled systems built with a large number of inexpensive physicalprocessors at the other end. Both kinds of distributed system are made availableby the rapid progress in the technology of large-scale integrated circuits. Yetlittle has been done in the research on semantics and programming methodologiesfor distributed information processing systems.Our main research goal is to understand and describe the behaviour of suchdistributed systems in seeking the maximum benefit of employing multi-processorcomputation schemata.Hayes, J.E., D. Michie, and L. I. Mikulich (Eds.), Machine Intelligence 9, Ellis Horwood.

Summary of Stanford Ph.D. dissertation, Computer Science Dept. Stanford University (1977).Artificial Intelligence 12(2): 73-119.

Boitet, C. 1977 Where Does GETA Stand at the Beginning of Brinkmann, K.-H.

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